Clinical Epigenetics最新文献

Inflammation underlies many conditions causing excess morbidity and mortality among people with HIV (PWH). A handful of single-trait epigenome-wide association studies (EWAS) have suggested that inflammation is associated with DNA methylation (DNAm) among PWH. Multi-trait EWAS may further improve statistical power and reveal pathways in common between different inflammatory markers. We conducted single-trait EWAS of three inflammatory markers (soluble CD14, D-dimers and interleukin-6) in the Veterans Aging Cohort Study (n = 920). The study population was all male PWH with an average age of 51 years, and 82.3% self-reported as Black. We then applied two multi-trait EWAS methods-CPASSOC and OmniTest-to combine single-trait EWAS results. CPASSOC and OmniTest identified 189 and 157 inflammation-associated DNAm sites, respectively, of which 112 overlapped. Among the identified sites, 56% were not significant in any single-trait EWAS. Top sites were mapped to inflammation-related genes including IFITM1, PARP9 and STAT1. These genes were significantly enriched in pathways such as "type I interferon signaling" and "immune response to virus." We demonstrate that multi-trait EWAS can improve the discovery of inflammation-associated DNAm sites, genes and pathways. These DNAm sites might hold the key to addressing persistent inflammation in PWH.

Background: Asthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma.

Methods: The Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood from 319 participants from 94 families. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 individuals. Principal component analysis on the clinical asthma markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates.

Results: 221 unique CpGs reached genome-wide significance at timepoint 1 after Bonferroni correction. PC7, which correlated with loadings of eosinophil counts and immunoglobulin levels, accounted for the majority of associations (204). Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points yielded a correlation of 0.81.

Conclusion: We identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to a robust DNA methylation profile as a new, stable biomarker for asthma.

Background: Epigenome-wide association studies have identified multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. This study aimed to test the hypothesis that an alcohol consumption epigenetic risk score (ERS) is associated with blood pressure (BP) traits.

Results: We implemented an ERS based on a previously reported epigenetic signature of 144 alcohol-associated CpGs in meta-analysis of participants of European ancestry. We found a one-unit increment of ERS was associated with eleven drinks of alcohol consumed per day, on average, across several cohorts (p < 0.0001). We examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with BP levels, i.e., a one-unit increase in ERS was associated with 0.74 mm Hg (p = 0.002) higher SBP and 0.50 mm Hg (p = 0.0006) higher DBP, but not with HTN. Longitudinal analyses in FHS (n = 3260) and five independent external cohorts (n = 4021) showed that the baseline ERS was not associated with a change in BP over time or with incident HTN.

Conclusions: Our findings demonstrate that the ERS has potential clinical utility in assessing lifestyle factors related to cardiovascular risk, especially when self-reported behavioral data (e.g., alcohol consumption) are unreliable or unavailable.

Background: Facioscapulohumeral dystrophy (FSHD) is a myopathy characterized by the loss of repressive epigenetic features affecting the D4Z4 locus (4q35). The assessment of DNA methylation at two regions (DUX4-PAS and DR1) of D4Z4 locus proved to be an effective method to detect epigenetic signatures compatible with FSHD. The present study aims at validating the employment of this method into clinical practice and improving the protocol by refining the classification thresholds of 4qA/4qA patients. To this purpose, 218 subjects with clinical suspicion of FSHD collected in 2022-2023 were analyzed. Each participant underwent in parallel the traditional FSHD molecular testing (D4Z4 sizing) and the proposed methylation assay. The results provided by both analyses were compared to evaluate the concordance and calculate the performance metrics of the methylation test.

Results: Among the 218 subjects, the 4q variant type distribution was 54% 4qA/4qA, 43% 4qA/4qB and 3% 4qB/4qB. The methylation analysis was performed only on carriers of at least one 4qA allele. After refining the classification threshold, the test reached the following performance metrics: sensitivity = 0.90, specificity = 1.00 and accuracy = 0.93. These results confirmed the effectiveness of the methylation assay in identifying patients with genetic signature compatible with FSHD1 and FSHD2 based on their DUX4-PAS and DR1 profile, respectively. The methylation data were also evaluated with respect to the clinical information.

Conclusions: The study confirmed the ability of the method to accurately identify methylation profiles compatible with FSHD genetic signatures considering the 4q genotype. Moreover, the test allows the detection of hypomethylated profiles in asymptomatic patients, suggesting its potential application in identifying preclinical conditions in patients with positive family history and FSHD genetic signatures. Furthermore, the present work emphasizes the importance of interpreting methylation profiles considering the patients' clinical data.

Background: Colorectal cancer is a public health issue and was the third leading cause of cancer-related death worldwide in 2022. Early diagnosis can improve prognosis, making screening a central part of colorectal cancer management. Blood-based screening, diagnosis and follow-up of colorectal cancer patients are possible with the study of cell-free circulating tumor DNA. This study aimed to identify novel DNA methylation biomarkers of colorectal cancer that can be used for the follow-up of patients with colorectal cancer.

Methods: A DNA methylation profile was established in the Gene Expression Omnibus (GEO) database (n = 507) using bioinformatics analysis and subsequently confirmed using The Cancer Genome Atlas (TCGA) database (n = 348). The in silico profile was then validated on local tissue and cell-free DNA samples using methylation-specific digital PCR in colorectal cancer patients (n = 35) and healthy donors (n = 35).

Results: The DNA methylation of COL25A1 and METAP1D was predicted to be a colorectal cancer biomarker by bioinformatics analysis (ROC AUC = 1, 95% CI [0.999-1]). The two biomarkers were confirmed with tissue samples, and the combination of COL25A1 and METAP1D yielded 49% sensitivity and 100% specificity for cell-free DNA.

Conclusion: Bioinformatics analysis of public databases revealed COL25A1 and METAP1D DNA methylation as clinically applicable liquid biopsies DNA methylation biomarkers. The specificity implies an excellent positive predictive value for follow-up, and the high sensitivity and relative noninvasiveness of a blood-based test make these biomarkers compatible with colorectal cancer screening. However, the clinical impact of these biomarkers in colorectal cancer screening and follow-up needs to be established in further prospective studies.

Background: DNA methylation profiling may provide a more accurate measure of the smoking status than self-report and may be useful in guiding clinical interventions and forensic investigations. In the current study, blood DNA methylation profiles of nearly 800 Polish individuals were assayed using Illuminia EPIC and the inference of smoking from epigenetic data was explored. In addition, we focused on the role of the AHRR gene as a top marker for smoking and investigated its responsiveness to other lifestyle behaviors.

Results: We found > 450 significant CpGs associated with cigarette consumption, and overrepresented in various biological functions including cell communication, response to stress, blood vessel development, cell death, and atherosclerosis. The model consisting of cg05575921 in AHRR (p = 4.5 × 10^-32) and three additional CpGs (cg09594361, cg21322436 in CNTNAP2 and cg09842685) was able to predict smoking status with a high accuracy of AUC = 0.8 in the test set. Importantly, a gradual increase in the probability of smoking was observed, starting from occasional smokers to regular heavy smokers. Furthermore, former smokers displayed the intermediate DNA methylation profiles compared to current and never smokers, and thus our results indicate the potential reversibility of DNA methylation after smoking cessation. The AHRR played a key role in a predictive analysis, explaining 21.5% of the variation in smoking. In addition, the AHRR methylation was analyzed for association with other modifiable lifestyle factors, and showed significance for sleep and physical activity. We also showed that the epigenetic score for smoking was significantly correlated with most of the epigenetic clocks tested, except for two first-generation clocks.

Conclusions: Our study suggests that a more rapid return to never-smoker methylation levels after smoking cessation may be achievable in people who change their lifestyle in terms of physical activity and sleep duration. As cigarette smoking has been implicated in the literature as a leading cause of epigenetic aging and AHRR appears to be modifiable by multiple exogenous factors, it emerges as a promising target for intervention and investment.

Epigenetic modifications control gene expression and are essential for turning genes on and off to regulate and maintain differentiated cell types. Epigenetics are also modified by a multitude of environmental exposures, including diet and pollutants, allowing an individual's environment to influence gene expression and resultant phenotypes and clinical outcomes. These epigenetic modifications due to gene-environment interactions can also be transmitted across generations, raising the possibility that environmental influences that occurred in one generation may be transmitted beyond the second generation, exerting a long-lasting effect. In this review, we cover the known mechanisms of epigenetic modification acquisition, reprogramming and persistence, animal models and human studies used to understand multigenerational epigenetic transmission, and examples of environmentally induced epigenetic change and its transmission across generations. We highlight the importance of environmental health not only on the current population but also on future generations that will experience health outcomes transmitted through epigenetic inheritance.

Background: A series of modifiable lifestyle factors, such as diet quality, physical activity, alcohol intake, and smoking, may drive the rising burden of type 2 diabetes (T2DM) among sub-Saharan Africans globally. It is unclear whether epigenetic changes play a mediatory role in the associations between these lifestyle factors and T2DM. We assessed the associations between a comprehensive lifestyle index, DNA methylation and T2DM among Ghanaian adults.

Methods: We used whole-blood Illumina 450 k DNA methylation data from 713 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. We constructed a comprehensive lifestyle index based on established cut-offs for diet quality, physical activity, alcohol intake, and smoking status. In the T2DM-free discovery cohort (n = 457), linear models were fitted to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with the lifestyle index after adjustment for age, sex, body mass index (BMI), and technical covariates. Associations between the identified DMPs and the primary outcome (T2DM), as well as secondary outcomes (fasting blood glucose (FBG) and HbA1c), were determined via logistic and linear regression models, respectively.

Results: In the present study population (mean age: 52 ± 10 years; male: 42.6%), the comprehensive lifestyle index showed a significant association with one DMP annotated to an intergenic region on chromosome 7 (false discovery rate (FDR) = 0.024). Others were annotated to ADCY7, SMARCE1, AHRR, LOXL2, and PTBP1 genes. One DMR was identified and annotated to the GFPT2 gene (familywise error rate (FWER) from bumphunter bootstrap = 0.036). None of the DMPs showed significant associations with T2DM; directions of effect were positive for the DMP in the AHRR and inverse for all the other DMPs. Higher methylation of the ADCY7 DMP was associated with higher FBG (p = 0.024); LOXL2 DMP was associated with lower FBG (p = 0.023) and HbA1c (p = 0.049); and PTBP1 DMP was associated with lower HbA1c (p = 0.002).

Conclusions: In this explorative epigenome-wide association study among Ghanaians, we identified one DMP and DMR associated with a comprehensive lifestyle index not previously associated with individual lifestyle factors. Based on our findings, we infer that lifestyle factors in combination, affect DNA methylation, thereby influencing the risk of T2DM among Ghanaian adults living in different contexts.

Background: The role of epigenetics in cardiovascular diseases has paved the way for innovative therapeutic approaches. Investigating epigenetic changes using cell-free DNA (cfDNA) holds substantial promise beyond mere diagnostics, especially for heart-related conditions like acute myocardial infarction (AMI), where obtaining tissue samples is a challenge. This study explores the methylation patterns of cfDNA in AMI patients and compares them with genomic DNA (gDNA) from the same individuals, aiming to evaluate the effectiveness of cfDNA as a valuable resource for studying heart-related diseases.

Methodology: We generated global methylome profiles of cfDNA and gDNA from 25 AMI patients using EM-Seq. Tissue deconvolution analysis was performed to estimate tissue specificity based on the methylation patterns. Differentially methylated loci were identified and explored to understand AMI pathophysiology.

Results: Comparative analysis of cfDNA and gDNA methylation patterns in AMI patients reveals cfDNA holds more significance than gDNA. Principal component analysis revealed distinct clusters for cfDNA and gDNA, indicating distinct methylome profiles. cfDNA originated from multiple sources, predominantly from neutrophils (~ 75%) and about 10% from the left atrium, highlighting cardiac-specific changes. In contrast, immune cells are the major source of gDNA, indicative of inflammatory responses. Gene set enrichment analysis (GSEA) associates cfDNA methylation patterns with pathways related to cardiac muscle contraction, inflammation, hypoxia, and lipid metabolism. The affected genes include G protein-coupled receptors (GHSR, FFAR2, HTR1A, and VIPR2) that are part of the cAMP signaling pathway.

Conclusion: Epigenetic changes in cfDNA are more specific to cardiac tissue compared to those in gDNA, providing better insights into the molecular mechanisms involved in AMI. Genes that are differentially methylated in cfDNA and regulate core pathways, such as cAMP signaling, could be targeted for clinical applications, including the development of effective biomarkers and therapeutic targets.