Clinical Epigenetics最新文献

Background: DNA methylation is a critical regulatory mechanism of gene expression, influencing various human diseases and traits. While traditional expression quantitative trait loci (eQTL) studies have helped elucidate the genetic regulation of gene expression, there is a growing need to explore environmental influences on gene expression. Existing methods such as PrediXcan and FUSION focus on genotype-based associations but overlook the impact of environmental factors. To address this gap, we present MOSES (methylation-based gene association), a novel approach that utilizes DNA methylation to identify environmentally regulated genes associated with traits or diseases without relying on measured gene expression.

Results: MOSES involves training, imputation, and association testing. It employs elastic-net penalized regression models to estimate the influence of CpGs and SNPs (if available) on gene expression. We developed and compared four MOSES versions incorporating different methylation and genetic data: (1) cis-DNA methylation within 1 Mb of promoter regions, (2) both cis-SNPs and cis-CpGs, 3) both cis- and a part of trans- CpGs (±5Mb away) from promoter regions), and 4) long-range DNA methylation (±10 Mb away) from promoter regions. Our analysis using nasal epithelium and white blood cell data from the Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR) study demonstrated that MOSES, particularly the version incorporating long-range CpGs (MOSES-DNAm 10 M), significantly outperformed existing methods like PrediXcan, MethylXcan, and Biomethyl in predicting gene expression. MOSES-DNAm 10 M identified more differentially expressed genes (DEGs) associated with atopic asthma, particularly those involved in immune pathways, highlighting its superior performance in uncovering environmentally regulated genes. Further application of MOSES to lung tissue data from idiopathic pulmonary fibrosis (IPF) patients confirmed its robustness and versatility across different diseases and tissues.

Conclusion: MOSES represents an innovative advancement in gene association studies, leveraging DNA methylation to capture the influence of environmental factors on gene expression. By incorporating long-range CpGs, MOSES-DNAm 10 M provides superior predictive accuracy and gene association capabilities compared to traditional genotype-based methods. This novel approach offers valuable insights into the complex interplay between genetics and the environment, enhancing our understanding of disease mechanisms and potentially guiding therapeutic strategies. The user-friendly MOSES R package is publicly available to advance studies in various diseases, including immune-related conditions like asthma.

Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. There is little understanding of why some organs are specifically impacted in patients and the mechanisms of disease persistence remain unclear. While much work has been done characterizing the DNA methylation status in SLE, there is less information on histone modifications, a more dynamic epigenetic feature. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets.

Results: We examined 20 patients with SLE and 8 controls and found that individual chromatin marks varied considerably across T cells, B cells, and monocytes. When pathways were examined, there was far more concordance with conservation of TNF, IL-2/STAT5, and KRAS pathways across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Signals also demonstrated significant overlap with GWAS signals in a manner that did not implicate one cell type more than the others.

Conclusions: The pathways identified by altered histone modifications and p300 binding are pathways known to be important from RNA expression studies and recognized pathogenic mechanisms of disease. NFκB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. Importantly, this NFκB pathway, so strongly implicated in the patients with generalized SLE, was much less impacted in monocytes when cutaneous lupus was compared to the general SLE cohort and also less impacted in lupus nephritis compared to general SLE. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.

Background: This study aimed to identify DNA methylation biomarkers associated with myopia using summary-data-based Mendelian randomization (SMR).

Methods: A systematic search of the PubMed, Web of Science, Cochrane Library, and Embase databases was conducted up to March 27, 2024. SMR analyses were performed to integrate genome-wide association study (GWAS) with methylation quantitative trait loci (mQTL) and expression quantitative trait loci (eQTL) studies. The heterogeneity in the dependent instrument (HEIDI) test was utilized to distinguish pleiotropic associations from linkage disequilibrium.

Results: The systematic review identified 26 DNA methylation biomarkers in five studies, with no overlap observed among those identified by different studies. After integrating GWAS with multi-omics data of mQTL and eQTL, six genes were significantly associated with myopia: PRMT6 (cg00944433 and cg15468180), SH3YL1 (cg03299269, cg11361895, and cg13354988), ZKSCAN4 (cg01192291), GATS (cg17830204), NPAT (cg04826772), and UBE2I (cg03545757 and cg08025960).

Conclusions: We identified six methylation biomarkers associated with the risk of myopia that may be helpful to elucidate the etiology mechanisms of myopia. Further experimental validation studies are required to corroborate these findings.

Background: We have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.

Methods: For this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.

Results: The updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.

Conclusions: The updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/ ) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.

TET2 is a critical gene that regulates DNA methylation, encoding a dioxygenase protein that plays a vital role in the regulation of genomic methylation and other epigenetic modifications, as well as in hematopoiesis. Mutations in TET2 are present in 7%-28% of adult acute myeloid leukemia (AML) patients. Despite this, the precise mechanisms by which TET2 mutations contribute to malignant transformation and how these insights can be leveraged to enhance treatment strategies for AML patients with TET2 mutations remain unclear. In this review, we provide an overview of the functions of TET2, the effects of its mutations, its role in clonal hematopoiesis, and the possible mechanisms of leukemogenesis. Additionally, we explore the mutational landscape across different AML subtypes and present recent promising preclinical research findings.

Background: Assay of Transposase Accessible Chromatin Sequencing (ATAC-seq) is a high-throughput sequencing technique that detects open chromatin regions across the genome. These regions are critical in facilitating transcription factor binding and subsequent gene expression. Herein, we utilized ATAC-seq to identify key molecular targets regulating the development and progression of hepatocellular carcinoma (HCC) and elucidate the underlying mechanisms.

Methods: We first compared chromatin accessibility profiles between HCC and normal tissues. Subsequently, RNA-seq data was employed to identify differentially expressed genes (DEGs). Integrating ATAC-seq and RNA-seq data allowed the identification of transcription factors and their putative target genes associated with differentially accessible regions (DARs). Finally, functional experiments were conducted to investigate the effects of the identified regulatory factors and corresponding targets on HCC cell proliferation and migration.

Results: Enrichment analysis of DARs between HCC and adjacent normal tissues revealed distinct signaling pathways and regulatory factors. Upregulated DARs in HCC were enriched in genes related to the MAPK and FoxO signaling pathways and associated with transcription factor families like ETS and AP-1. Conversely, downregulated DARs were associated with the TGF-β, cAMP, and p53 signaling pathways and the CTCF family. Integration of the datasets revealed a positive correlation between specific DARs and DEGs. Notably, PRPF3 emerged as a gene associated with DARs in HCC, and functional assays demonstrated its ability to promote HCC cell proliferation and migration. To the best of our knowledge, this is the first report highlighting the oncogenic role of PRPF3 in HCC. Furthermore, ZNF93 expression positively correlated with PRPF3, and ChIP-seq data indicated its potential role as a transcription factor regulating PRPF3 by binding to its promoter region.

Conclusion: This study provides a comprehensive analysis of the epigenetic landscape in HCC, encompassing both chromatin accessibility and the transcriptome. Our findings reveal that ZNF93 promotes the proliferation and motility of HCC cells through transcriptional regulation of a novel oncogene, PRPF3.

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.