Cytosine-phosphate-guanine Sites Research Articles

Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) has been a leading cause of cancer-related mortality worldwide. Early intervention can significantly improve prognosis. DNA methylation could occur in the early stage of tumor. Comprehensive understanding the epigenetic landscape of early-stage LUAD is crucial in understanding tumorigenesis.MethodsEnzymatic methyl sequencing (EM-seq) was performed on 23 tumors and paired normal tissue to reveal distinct epigenetic landscape, for compared with The Cancer Genome Atlas (TCGA) 450K methylation microarray data. Then, an integrative analysis was performed combined with TCGA LUAD RNA-seq data to identify significant differential methylated and expressed genes. Subsequently, the prognostic risk model was constructed and cellular composition was analyzed.ResultsMethylome analysis of EM-seq comparing tumor and normal tissues identified 25 million cytosine-phosphate-guanine (CpG) sites and 30,187 differentially methylated regions (DMR) with a greater number of untraditional types. EM-seq identified a significantly higher number of CpG sites and DMRs compared to the 450K microarray. By integrating the differentially methylated genes (DMGs) with LUAD-related differentially expressed genes (DEGs) from the TCGA database, we constructed prognostic model based on six differentially methylated-expressed genes (MEGs) and verified our prognostic model in GSE13213 and GSE42127 dataset. Finally, cell deconvolution based on the in-house EM-seq methylation profile was used to estimate cellular composition of early-stage LUAD.ConclusionsThis study firstly delves into novel pattern of epigenomic DNA methylation and provides a multidimensional analysis of the role of DNA methylation revealed by EM-seq in early-stage LUAD, providing distinctive insights into its potential epigenetic mechanisms.

DNA methylation of skeletal muscle function-related secretary factors identifies FGF2 as a potential biomarker for sarcopenia.

Sarcopenia is characterized by progressive loss of muscle mass and function due to aging. DNA methylation has been identified to play important roles in the dysfunction of skeletal muscle. The aim of our present study was to explore the whole blood sample-based methylation changes of skeletal muscle function-related factors in patients with sarcopenia. The overall DNA methylation levels were analysed by using MethlTarget™ DNA Methylation Analysis platform in a discovery set consistent of 50 sarcopenic older adults (aged ≥65years) and 50 age- and sex-matched non-sarcopenic individuals. The candidate differentially methylated regions (DMRs) were further validated by Methylation-specific PCR (MSP) in another two independent larger sets and confirmed by pyrosequencing. Receiver operating characteristic (ROC) curve analysis was used to determine the optimum cut-off levels of fibroblast growth factor 2 (FGF2)_30 methylation best predicting sarcopenia and area under the ROC curve (AUC) was measured. The correlation between candidate DMRs and the risk of sarcopenia was investigated by univariate analysis and multivariate logistic regression analysis. Among 1149 cytosine-phosphate-guanine (CpG) sites of 27 skeletal muscle function-related secretary factors, 17 differentially methylated CpG sites and 7 differentially methylated regions (DMRs) were detected between patients with sarcopenia and control subjects in the discovery set. Further methylation-specific PCR identified that methylation of fibroblast growth factor 2 (FGF2)_30 was lower in patients with sarcopenia and the level was decreased as the severity of sarcopenia increased, which was confirmed by pyrosequencing. Correlation analysis demonstrated that the methylation level of FGF2_30 was positively correlated to ASMI (r=0.372, P<0.001), grip strength (r=0.334, P<0.001), and gait speed (r=0.411, P<0.001). ROC curve analysis indicated that the optimal cut-off value of FGF2_30 methylation level that predicted sarcopenia was 0.15 with a sensitivity of 84.6% and a specificity of 70.1% (AUC=0.807, 95% CI=0.756-0.858, P<0.001). Multivariate logistic regression analyses showed that lower FGF2_30 methylation level (<0.15) was significantly associated with increased risk of sarcopenia even after adjustment for potential confounders including age, sex, and BMI (adjusted OR=9.223, 95% CI: 6.614-12.861, P<0.001). Our results suggest that lower FGF2_30 methylation is correlated with the risk and severity of sarcopenia in the older adults, indicating that FGF2 methylation serve as a surrogate biomarker for the screening and evaluation of sarcopenia.

Gbdmr: identifying differentially methylated CpG regions in the human genome via generalized beta regressions

BackgroundDNA methylation is a biochemical process in which a methyl group is added to the cytosine-phosphate-guanine (CpG) site on DNA molecules without altering the DNA sequence. Multiple CpG sites in a certain genome region can be differentially methylated across phenotypes. Identifying these differentially methylated CpG regions (DMRs) associated with the phenotypes contributes to disease prediction and precision medicine development.ResultsWe propose a novel DMR detection algorithm, gbdmr. In contrast to existing methods under a linear regression framework, gbdmr assumes that DNA methylation levels follow a generalized beta distribution. We compare gbdmr to alternative approaches via simulations and real data analyses, including dmrff, a new DMR detection approach that shows promising performance among competitors, and the traditional EWAS that focuses on single CpG sites. Our simulations demonstrate that gbdmr is superior to the other two when the correlation between neighboring CpG sites is strong, while dmrff shows a higher power when the correlation is weak. We provide an explanation of these phenomena from a theoretical perspective. We further applied the three methods to multiple real DNA methylation datasets. One is from a birth cohort study undertaken on the Isle of Wight, United Kingdom, and the other two are from the Gene Expression Omnibus database repository. Overall, gbdmr identifies more DMR CpGs linked to phenotypes than dmrff, and the simulated results support the findings.ConclusionsGbdmr is an innovative method for detecting DMRs based on generalized beta regression. It demonstrated notable advantages over dmrff and traditional EWAS, particularly when adjacent CpGs exhibited moderate to strong correlations. Our real data analyses and simulated findings highlight the reliability of gbdmr as a robust DMR detection tool. The gbdmr approach is accessible and implemented by R on GitHub: https://github.com/chengzhouwu/gbdmr.

APOE genotype-specific methylation patterns are linked to Alzheimer disease pathology and estrogen response

The joint effects of APOE genotype and DNA methylation on Alzheimer disease (AD) risk is relatively unknown. We conducted genome-wide methylation analyses using 2,021 samples in blood (91 AD cases, 329 mild cognitive impairment, 1,391 controls) and 697 samples in brain (417 AD cases, 280 controls). We identified differentially methylated levels in AD compared to controls in an APOE genotype-specific manner at 25 cytosine-phosphate-guanine (CpG) sites in brain and 36 CpG sites in blood. Additionally, we identified seven CpG sites in the APOE region containing TOMM40, APOE, and APOC1 genes with P < 5 × 10−8 between APOE ε4 carriers and non-carriers in brain or blood. In brain, the most significant CpG site hypomethylated in ε4 carriers compared to non-carriers was from the TOMM40 in the total sample, while most of the evidence was derived from AD cases. However, the CpG site was not significantly modulating expression of these three genes in brain. Three CpG sites from the APOE were hypermethylated in APOE ε4 carriers in brain or blood compared in ε4 non-carriers and nominally significant with APOE expression in brain. Three CpG sites from the APOC1 were hypermethylated in blood, which one of the 3 CpG sites significantly lowered APOC1 expression in blood using all subjects or ε4 non-carriers. Co-methylation network analysis in blood and brain detected eight methylation networks associated with AD and APOE ε4 status. Five of the eight networks included genes containing network CpGs that were significantly enriched for estradiol perturbation, where four of the five networks were enriched for the estrogen response pathway. Our findings provide further evidence of the role of APOE genotype on methylation levels associated with AD, especially linked to estrogen response pathway.

Prediction of methylation status using WGS data of plasma cfDNA for multi-cancer early detection (MCED)

BackgroundCell-free DNA (cfDNA) contains a large amount of molecular information that can be used for multi-cancer early detection (MCED), including changes in epigenetic status of cfDNA, such as cfDNA fragmentation profile. The fragmentation of cfDNA is non-random and may be related to cfDNA methylation. This study provides clinical evidence for the feasibility of inferring cfDNA methylation levels based on cfDNA fragmentation patterns. We performed whole-genome bisulfite sequencing and whole-genome sequencing (WGS) on both healthy individuals and cancer patients. Using the information of whole-genome methylation levels, we investigated cytosine–phosphate–guanine (CpG) cleavage profile and validated the method of predicting the methylation level of individual CpG sites using WGS data.ResultsWe conducted CpG cleavage profile biomarker analysis on data from both healthy individuals and cancer patients. We obtained unique or shared potential biomarkers for each group and built models accordingly. The modeling results proved the feasibility to predict the methylation status of single CpG sites in cfDNA using cleavage profile model from WGS data.ConclusionBy combining cfDNA cleavage profile of CpG sites with machine learning algorithms, we have identified specific CpG cleavage profile as biomarkers to predict the methylation status of individual CpG sites. Therefore, methylation profile, a widely used epigenetic biomarker, can be obtained from a single WGS assay for MCED.

Identification of candidate DNA methylation biomarkers related to Alzheimer’s disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Integrated Analyses of Single-Cell Transcriptome and Mendelian Randomization Reveal the Protective Role of Resistin in Sepsis Survival in Intensive Care Unit.

The high morbidity and mortality rates associated with sepsis highlight the challenges of finding specific remedies for this condition in the intensive care unit (ICU). This study aimed to explore the differentially expressed genes (DEGs) specific to cell types in sepsis and investigate the role of resistin in the survival of sepsis patients through Mendelian randomization (MR) analyses. We used single-cell and bulk transcriptome data to identify cell type-specific DEGs between sepsis and healthy controls. MR analyses were then conducted to investigate the causal relationships between resistin (one of the identified DEGs) levels and the survival of sepsis patients. Additionally, we utilized meQTL (methylation quantitative trait loci) to identify cytosine-phosphate-guanine (CpG) sites that may directly affect sepsis. We identified 560 cell type-specific DEGs between sepsis and healthy controls. Notably, we observed the upregulation of resistin levels in macrophages during sepsis. In bulk transcriptome, RETN is also upregulated in sepsis samples compared with healthy controls. MR analyses revealed a negative association existed between the expression of resistin, at both gene and protein levels, and the mortality or severity of sepsis patients in ICU. Moreover, there were no associations observed between resistin levels and death or organ failure due to other causes. We also identified three methylation CpG sites, located in RETN or its promoter region-cg06633066, cg22322184, and cg02346997-that directly affected both resistin protein levels and sepsis death in the ICU. Our findings suggest that resistin may provide feasible protection for sepsis patients, particularly those with severe cases, without serious side effects. Therefore, resistin could be a potential drug candidate for sepsis treatment. Additionally, we identified two CpG sites, cg06633066 and cg22322184, that were associated with RETN protein levels and sepsis death, providing novel insights into the underlying mechanisms of sepsis.

Altered DNA Methylation of the Serotonin Transporter Gene Associated with Early Life Stress and White Matter Microalterations in Korean Patients with Panic Disorder

Introduction: Changes in the DNA methylation of 5-HTTLPR are associated with the pathophysiology of panic disorder (PD). This study was conducted to investigate the association between stressful life events and the level of 5-HTTLPR methylation in patients with PD. We also examined whether these factors were associated with white matter alterations in psychological trauma-related regions. Methods: The participants comprised 232 patients with PD and 93 healthy adults of Korean descent. DNA methylation levels of five cytosine-phosphate-guanine (CpG) sites in the 5-HTTLPR region were analyzed. Voxel-wise statistical analysis of diffusion tensor imaging data was performed within the trauma-related regions. Results: PD patients showed significantly lower levels of the DNA methylation at 5-HTTLPR 5 CpG sites than healthy controls. In patients with PD, the DNA methylation levels at 5-HTTLPR 5 CpG sites showed significant negative association with the parental separation-related psychological distress, and positive correlations with the fractional anisotropy values of the superior longitudinal fasciculus (SLF) which might be related to trait anxiety. Conclusion: Early life stress was significantly associated with DNA methylation levels at 5-HTTLPR related to the decreased white matter integrity in the SLF region in PD. Decreased white matter connectivity in the SLF might be related to trait anxiety and is vital to the pathophysiology of PD.

Identification of a novel PARP4 gene promoter CpG locus associated with cisplatin chemoresistance

The protein family of poly (ADP-ribose) polymerases (PARPs) is comprised of multifunctional nuclear enzymes. Several PARP inhibitors have been developed as new anticancer drugs to combat resistance to chemotherapy. Herein, we characterized PARP4 mRNA expression profiles in cisplatin-sensitive and cisplatin-resistant ovarian cancer cell lines. PARP4 mRNA expression was significantly upregulated in cisplatin-resistant ovarian cancer cell lines, and this upregulation was associated with hypomethylation of specific cytosine-phosphate-guanine (CpG) sites (cg18582260 and cg17117459) on its promoter. Reduced PARP4 expression was restored by treating cisplatin-sensitive cell lines with a demethylation agent, implicating epigenetic regulation of PARP4 expression by promoter methylation. Depletion of PARP4 expression in cisplatin-resistant cell lines reduced cisplatin chemoresistance and promoted cisplatin-induced DNA fragmentation. The differential mRNA expression and DNA methylation status at specific PARP4 promoter CpG sites (cg18582260 and cg17117459) according to cisplatin responses, were further validated in primary ovarian tumor tissues. The results showed significantly increased PARP4 mRNA expressions and decreased DNA methylation levels at specific PARP4 promoter CpG sites (cg18582260 and cg17117459) in cisplatin-resistant patients. Additionally, the DNA methylation status at cg18582260 CpG sites in ovarian tumor tissues showed fairly clear discrimination between cisplatin-resistant patients and cisplatin-sensitive patients, with high accuracy (area under the curve = 0.86, p = 0.003845). Our findings suggested that the DNA methylation status of PARP4 at the specific promoter site (cg18582260) may be a useful diagnostic biomarker for predicting the response to cisplatin in ovarian cancer patients.

Age estimation based on blood DNA methylation levels in brown bears.

Age is an essential trait for understanding the ecology and management of wildlife. A conventional method of estimating age in wild animals is counting annuli formed in the cementum of teeth. This method has been used in bears despite some disadvantages, such as high invasiveness and the requirement for experienced observers. In this study, we established a novel age estimation method based on DNA methylation levels using blood collected from 49 brown bears of known ages living in both captivity and the wild. We performed bisulfite pyrosequencing and obtained methylation levels at 39 cytosine-phosphate-guanine (CpG) sites adjacent to 12 genes. The methylation levels of CpGs adjacent to four genes showed a significant correlation with age. The best model was based on DNA methylation levels at just four CpG sites adjacent to a single gene, SLC12A5, and it had high accuracy with a mean absolute error of 1.3 years and median absolute error of 1.0 year after leave-one-out cross-validation. This model represents the first epigenetic method of age estimation in brown bears, which provides benefits over tooth-based methods, including high accuracy, less invasiveness, and a simple procedure. Our model has the potential for application to other bear species, which will greatly improve ecological research, conservation, and management.

DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in blood

BackgroundFibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. ObjectivesTo perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. MethodsWe performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. ResultsWe identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10−7) and EPIC arrays (p < 5.78 × 10−8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. ConclusionWe identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.

Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n= 17,034), replicated these findings in the Women's Health Initiative (WHI, n= 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p<1E-7) and 1,238 replicated in the WHI (FDR<0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood

Alzheimer’s disease (AD) is the leading cause of dementia worldwide. Mild cognitive impairment (MCI) is an early stage of mental decline that can precede the development of AD. Oftentimes, the progression of MCI to AD is difficult to predict. An AD diagnosis can involve invasive brain scans and spinal fluid tests. However, one promising biomarker for the diagnosis of AD is epigenetic data, specifically the methylation level of cytosine-phosphate-guanine (CpG) sites in the DNA. AD is linked to environmental factors, with some factors causing changes in these DNA methylation levels. We hypothesized that machine learning models can use blood DNA methylation levels, sex, and age to predict between cognitive normality, MCI, and AD with at least 50% accuracy. In this paper, we generated four machine learning models and two dataset dimensionality reduction methods in order to test this hypothesis. We trained the models on data from CpG sites from whole blood. When predicting if a patient would be cognitively normal, have MCI, or have AD, we achieved an accuracy of 53.33%, which is 20% greater than random guessing. We achieved this accuracy using a gradient boosting decision trees model in combination with a logistic regression method for feature selection. While this accuracy is low, the feature selection method that we developed may be useful in future research, as it identifies CpG sites that are most correlated with AD. Since peripheral blood is easily accessible through blood draw, our model represents a practical way to assist in the diagnosis of AD.

LINE-1 hypomethylation is associated with poor outcomes in locoregionally advanced oropharyngeal cancer

Background and purposeCurrently, human papillomavirus (HPV) positivity represents a strong prognostic factor for both reduced risk of relapse and improved survival in patients with oropharyngeal squamous cell carcinoma (OPSCC). However, a subset of HPV-positive OPSCC patients still experience poor outcomes. Furthermore, HPV-negative OPSCC patients, who have an even higher risk of relapse, are still lacking suitable prognostic biomarkers for clinical outcome. Here, we evaluated the prognostic value of LINE-1 methylation level in OPSCC patients and further addressed the relationship between LINE-1 methylation status and p53 protein expression as well as genome-wide/gene-specific DNA methylation.ResultsIn this study, DNA was extracted from 163 formalin-fixed paraffin-embedded tissue samples retrospectively collected from stage III-IVB OPSCC patients managed with curative intent with up-front treatment. Quantitative methylation-specific PCR revealed that LINE-1 hypomethylation was directly associated with poor prognosis (5-year overall survival—OS: 28.1% for LINE-1 methylation < 35% vs. 69.1% for ≥ 55%; p < 0.0001). When LINE-1 methylation was dichotomized as < 55% versus ≥ 55%, interaction with HPV16 emerged: compared with hypermethylated HPV16-positive patients, subjects with hypomethylated HPV16-negative OPSCC reported an adjusted higher risk of death (HR 4.83, 95% CI 2.24–10.38) and progression (HR 4.54, 95% CI 2.18–9.48). Tumor protein p53 (TP53) gene is often mutated and overexpressed in HPV-negative OPSCC. Since p53 has been reported to repress LINE-1 promoter, we then analyzed the association between p53 protein expression and LINE-1 methylation levels. Following p53 immunohistochemistry, results indicated that among HPV16-negative patients with p53 ≥ 50%, LINE-1 methylation levels declined and remained stable at approximately 43%; any HPV16-positive patient reported p53 ≥ 50%. Finally, DNA methylation analysis demonstrated that genome-wide average methylation level at cytosine–phosphate–guanine sites was significantly lower in HPV16-negative OPSCC patients who relapsed within two years. The subsequent integrative analysis of gene expression and DNA methylation identified 20 up-regulated/hypomethylated genes in relapsed patients, and most of them contained LINE-1 elements in their promoter sequences.ConclusionsEvaluation of the methylation level of LINE-1 may help in identifying the subset of OPSCC patients with bad prognosis regardless of their HPV status. Aberrant LINE-1 hypomethylation might occur along with TP53 mutations and lead to altered gene expression in OPSCC.

Blood MAPT expression and methylation status in Alzheimer's disease

AbstractAimThis study aimed to investigate the expression levels and methylation status of microtubule‐associated protein tau (MAPT) in the blood of Alzheimer's disease (AD) patients and age‐ and sex‐matched healthy controls.MethodsFifty AD outpatients and 50 healthy contorls were enrolled. Blood samples were collected for processing of complementary DNA and genomic DNA. MAPT messenger ribonucleic acid (mRNA) expression was analyzed by real‐time quantitative polymerase chain reaction. The methylation rates of four cytosine‐phosphate‐guanine (CpG) sites in the upstream region of MAPT exon1 were evaluated by the pyrosequencing method.ResultsNo significant differences in MAPT mRNA expression levels were found between AD and control subjects (AD 0.97 ± 0.49 vs. control 1.0 ± 0.64, p = 0.62). MAPT mRNA expression levels were not correlated with any other clinical characteristics or results of psychological tests. MAPT mRNA expression levels were significantly higher in AD subjects treated with acetylcholinesterase inhibitors (AchEIs) (n = 25) than in subjects not treated with AChEIs (n = 25) (unmedicated 0.83 ± 0.33 vs. medicated 1.12 ± 0.59, p = 0.049). The AD subjects did not differ from the control subjects in methylation rates at selected CpG sites. MAPT methylation status were not correlated with clinical characteristics, the results of psychological tests, or MAPT mRNA expression.ConclusionMAPT mRNA expression levels and methylation status in blood do not appear useful as biomarkers for AD or the examined CpG sites were not genetically significant for MAPT gene expression or AD pathology. However, AChEIs may alter MAPT mRNA expression. Further studies are needed to explore blood biomarkers that can discriminate AD patients from controls.

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study

BackgroundEnvironmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window. ObjectivesThis study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort. MethodsWe repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data. ResultsWe included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease. ConclusionsThis study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

A correlation map of genome-wide DNA methylation patterns between paired human brain and buccal samples

Epigenome-wide association studies (EWAS) assessing the link between DNA methylation (DNAm) and phenotypes related to structural brain measures, cognitive function, and neurodegenerative diseases are becoming increasingly more popular. Due to the inaccessibility of brain tissue in humans, several studies use peripheral tissues such as blood, buccal swabs, and saliva as surrogates. To aid the functional interpretation of EWAS findings in such settings, there is a need to assess the correlation of DNAm variability across tissues in the same individuals. In this study, we performed a correlation analysis between DNAm data of a total of n = 120 matched post-mortem buccal and prefrontal cortex samples. We identified nearly 25,000 (3% of approximately 730,000) cytosine-phosphate-guanine (CpG) sites showing significant (false discovery rate q < 0.05) correlations between buccal and PFC samples. Correlated CpG sites showed a preponderance to being located in promoter regions and showed a significant enrichment of being determined by genetic factors, i.e. methylation quantitative trait loci (mQTL), based on buccal and dorsolateral prefrontal cortex mQTL databases. Our novel buccal–brain DNAm correlation map will provide a valuable resource for future EWAS using buccal samples for studying DNAm effects on phenotypes relating to the brain. All correlation results are made freely available to the public online.

Integrated Analysis of Gene Expression and Methylation Data to Identify Potential Biomarkers Related to Atherosclerosis Onset.

Atherosclerosis is a kind of chronic inflammatory cardiovascular disease. Epigenetic regulation plays a crucial role in atherosclerosis. Our study was aimed at finding potential biomarkers associated with the occurrence of atherosclerosis. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. The epigenome-wide association study (EWAS) analysis was performed on methylation data using CpGassoc package. The differential expression analysis was conducted on mRNA data using limma package. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment was done in clusterProfiler package. Finally, the logistic regression model was constructed using generalized linear model (glm) function. Between atherosclerotic vs. nonatherosclerotic samples, totally 4980 cytosine-phosphate-guanine (CpG) sites (annotated to 2860 genes) and 132 differentially expressed genes (DEGs) related to atherosclerosis were identified. The annotated 2860 genes and 132 DEGs were significantly enriched in 9 and 4 KEGG pathways and 289 and 132 GO terms, respectively. After cross-analysis, 6 crucial CpG sites were screened to build the model, including cg01187920, cg03422911, cg08018825, cg10967350, cg14473924, and cg25313204. The diagnostic model could reliably separate the atherosclerosis samples from nonatherosclerotic samples. In conclusion, the 6 CpG sites are probably potential diagnostic biomarkers for atherosclerosis, including cg01187920, cg03422911, cg08018825, cg10967350, cg14473924, and cg25313204.

A systematic review and metaanalysis of observational studies on the effects of epigenetic factors on serum triglycerides.

Epigenetic modifications might be associated with serum triglycerides (TG) levels. This study aims to systematically review the studies on the relationship between the methylation of specific cytosine-phosphate-guanine (CpG) sites and serum TG levels. This systematic review and meta-analysis study was conducted according to the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. A systematic literature search was conducted in Medline database (PubMed), Scopus, and Cochrane library up to end of 2020. All observational studies (cross-sectional, case-control, and cohort) were included. Studies that assessed the effect of DNA methylation of different CpG sites of ABCG1, CPT1A, and SREBF1 genes on serum TG levels were selected. The National Institutes of Health (NIH) checklist was used to assess the quality of included articles. Among 2790 articles, ten studies were included in the quantitative analysis and fourteen studies were included in the systematic review. DNA methylation of ABCG1 gene had significant positive association with TG levels (β = 0.05, 95% CI = 0.04, 0.05, P heterogeneity < 0.001). There was significant inverse association between DNA methylation of CPT1A gene and serum TG levels (β = -0.03, 95% CI = -0.03, -0.02, P heterogeneity < 0.001). DNA methylation of SREBF1 gene was positively and significantly associated with serum TG levels (β = 0.03; 95% CI = 0.02-0.04, P heterogeneity < 0.001). DNA methylation of ABCG1 and SREBF1 genes has positive association with serum TG level, whereas this association is opposite for CPT1A gene. The role of epigenetic factors should be considered in some populations with high prevalence of hypertriglyceridemia.

Gaseous air pollutants and DNA methylation in a methylome-wide association study of an ethnically and environmentally diverse population of U.S. adults

Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO2; NOx), ozone (O3), and sulfur dioxide (SO2) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation- and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (PCochran's Q > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a −0.3 (95% CI: −0.4, −0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a −0.3 (95% CI: −0.4, −0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression.