Clinical Epigenetics最新文献

Background: Biological age, especially epigenetic age derived from the epigenetic clock, is a significant measure of aging, considering the differences in aging rates among individuals. The epigenetic clock, a machine learning-based algorithm, uses DNA methylation states to estimate biological age. Previous studies have reported inconsistent associations between physical activity (PA) and the epigenetic clock, especially second-generation clocks such as PhenoAge and GrimAge. This study aimed to clarify this relationship using cross-sectional data from Japanese participants aged 40-69.

Methods: We used two datasets from the Saga J-MICC study, of which 867 samples were available for analysis. DNA methylation data from peripheral blood samples were used to calculate the epigenetic age using the epigenetic clocks PhenoAge and GrimAge. PA and sedentary time were measured using a single-axis accelerometer, while self-reported PA, sedentary time, and covariates were assessed using a self-administered questionnaire. The association between PA or sedentary time and epigenetic age acceleration was assessed using multiple linear regression.

Results: Pearson's correlation coefficients between accelerometer-based and self-reported PA variables ranged from 0.09 to 0.20. Multivariable regression analysis showed that accelerometer-based PA and sedentary time were associated with epigenetic age decelerations and accelerations, respectively. However, self-reported PA was not associated with the epigenetic age accelerations.

Conclusions: These results indicate that reducing sedentary time and increasing PA were associated with slowing both PhenoAge and GrimAge, even in East Asian populations with different exercise habits, body shapes, and lifestyles. This study highlights the potential of objective second-generation epigenetic age acceleration as an outcome index for healthcare interventions and clinical applications.

Background: Lack of insight into factors that determine purity and quality of human iPSC (hiPSC)-derived neo-cartilage precludes applications of this powerful technology toward regenerative solutions in the clinical setting. Here, we set out to generate methylome-wide landscapes of hiPSC-derived neo-cartilages from different tissues-of-origin and integrated transcriptome-wide data to identify dissimilarities in set points of methylation with associated transcription and the respective pathways in which these genes act.

Methods: We applied in vitro chondrogenesis using hiPSCs generated from two different tissue sources: skin fibroblasts and articular cartilage. Upon differentiation toward chondrocytes, these are referred to as hFiCs and hCiC, respectively. Genome-wide DNA methylation and RNA sequencing datasets were generated of the hiPSC-derived neo-cartilages, and the epigenetically regulated transcriptome was compared to that of neo-cartilage deposited by human primary articular cartilage (hPAC).

Results: Methylome-wide landscapes of neo-cartilages of hiPSCs reprogrammed from two different somatic tissues were 85% similar to that of hPACs. By integration of transcriptome-wide data, differences in transcriptionally active CpGs between hCiC relative to hPAC were prioritized. Among the CpG-gene pairs lower expressed in hCiCs relative to hPACs, we identified genes such as MGP, GDF5, and CHAD enriched in closely related pathways and involved in cartilage development that likely mark phenotypic differences in chondrocyte states. Vice versa, among the CpG-gene pairs higher expressed, we identified genes such as KIF1A or NKX2-2 enriched in neurogenic pathways and likely reflecting off target differentiation.

Conclusions: We did not find significant variation between the neo-cartilages derived from hiPSCs of different tissue sources, suggesting that application of a robust differentiation protocol such as we applied here is more important as compared to the epigenetic memory of the cells of origin. Results of our study could be further exploited to improve quality, purity, and maturity of hiPSC-derived neo-cartilage matrix, ultimately to realize introduction of sustainable, hiPSC-derived neo-cartilage implantation into clinical practice.

Background: Malignant cells exhibit reduced period circadian regulator 3 (PER3) expression. However, the underlying mechanisms of variations in PER3 expression in cancers and the specific function of PER3 in tumor progression remain poorly understood.

Results: We explored multiple public databases, conducted bioinformatics analyses, and performed in vitro and in vivo experiments for validation. We found PER3 expression was decreased in most types of cancers, and PER3 downregulation was associated with a poor prognosis in 8 types of cancer. PER3 promoter methylation levels were increased in 11 types of cancer. Promoter hypermethylation (CpG islands [CGIs] cg12258811 and cg14204433) correlated with decreased PER3 expression in six cancers (breast invasive carcinoma, colon adenocarcinoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma [KIRP], lung adenocarcinoma [LUAD], and uterine corpus endometrial carcinoma). CGI cg12258811 hypermethylation was associated with reduced survival time and advanced cancer stages. Moreover, the bisulfite pyrosequencing assay confirmed CGI cg12258811 hypermethylation and its negative correlation with PER3 expression. In vitro and in vivo experiments demonstrated that PER3 inhibited KIRP and LUAD progression. Decitabine enhanced PER3 expression and inhibited KIRP cell functions by reducing promoter (cg12258811) methylation level.

Conclusions: Our findings advanced the mechanistic understanding of variations in PER3 expression in cancers and confirmed the tumor-associated function of PER3 hypermethylation and downregulation.

Background: DNA methylation plays a critical role in asthma development, but differences in DNA methylation among adults with varying asthma severity are less well-defined.

Objective: To examine how DNA methylomic patterns differ among adults with asthma based on asthma severity and airway inflammation.

Methods: Peripheral blood T cells from 35 adults with asthma in Beijing, China, were serially collected over time (130 samples total) and analyzed for global DNA methylation using the Illumina MethylationEPIC Array. Differential methylation was compared among subjects with varying airway inflammation and severity, as measured by fraction of exhaled nitric oxide, forced expiratory volume in one second (FEV1), and Asthma Control Test (ACT) scores.

Results: Significant differences in DNA methylation were noted among subjects with different degrees of airway inflammation and asthma severity. These differences in DNA methylation were annotated to genes that were enriched in pathways related to asthma or T cell function and included gene ontology categories related to MHC class II assembly, T cell activation, interleukin (IL)-1, and IL-12. Genes related to P450 drug metabolism, glutathione metabolism, and developmental pathways were also differentially methylated in comparisons between subjects with high vs low FEV1 and ACT. Notable genes that were differentially methylated based on asthma severity included RUNX3, several members of the HLA family, AGT, PTPRC, PTPRJ, and several genes downstream of the JAK2 and TNF signaling pathway.

Conclusion: These findings demonstrate how adults with asthma of varying severity possess differences in peripheral blood T cell DNA methylation that contribute to differences in clinical indices of asthma.

Background: Multi-locus imprinting disturbance (MLID) with methylation defects in various differentially methylated regions (DMRs) has recently been identified in approximately 150 cases with imprinting disorders (IDs), and deleterious variants have been found in genes related to methylation maintenance of DMRs, such as those encoding proteins constructing the subcortical maternal complex (SCMC), in a small fraction of patients and/or their mothers. However, integrated methylation analysis for DMRs and sequence analysis for MLID-causative genes in MLID cases and their mothers have been performed only in a single study focusing on Beckwith-Wiedemann syndrome (BWS) and Silver-Russell syndrome (SRS) phenotypes.

Results: Of 783 patients with various IDs we have identified to date, we examined a total of 386 patients with confirmed epimutation and 71 patients with epimutation or uniparental disomy. Consequently, we identified MLID in 29 patients with epimutation confirmed by methylation analysis for multiple ID-associated DMRs using pyrosequencing and/or methylation-specific multiple ligation-dependent probe amplification. MLID was detected in approximately 12% of patients with BWS phenotype and approximately 5% of patients with SRS phenotype, but not in patients with Kagami-Ogata syndrome, Prader-Willi syndrome, or Angelman syndrome phenotypes. We next conducted array-based methylation analysis for 78 DMRs and whole-exome sequencing in the 29 patients, revealing hypomethylation-dominant aberrant methylation patterns in various DMRs of all the patients, eight probably deleterious variants in genes for SCMC in the mothers of patients, and one homozygous deleterious variant in ZNF445 in one patient. These variants did not show gene-specific methylation disturbance patterns. Clinically, neurodevelopmental delay and/or intellectual developmental disorder (ND/IDD) was observed in about half of the MLID patients, with no association with the identified methylation disturbance patterns and genetic variants. Notably, seven patients with BWS phenotype were conceived by assisted reproductive technology (ART).

Conclusions: The frequency of MLID was 7.5% (29/386) in IDs caused by confirmed epimutation. Furthermore, we revealed diverse patterns of hypomethylation-dominant methylation defects, nine deleterious variants, ND/IDD complications in about half of the MLID patients, and a high frequency of MLID in ART-conceived patients.

Objective: As the global use of extracorporeal membrane oxygenation (ECMO) treatment increases, survival rates have not correspondingly improved, emphasizing the need for refined patient selection to optimize resource allocation. Currently, prognostic markers at the molecular level are limited.

Methods: Thirty-four cardiogenic shock (CS) patients were prospectively enrolled, and peripheral blood mononuclear cells (PBMCs) were collected at the initiation of ECMO (t0), two-hour post-installation (t2), and upon removal of ECMO (tr). The PBMCs were analyzed by comprehensive epigenomic assays. Using the Wilcoxon signed-rank test and least absolute shrinkage and selection operator (LASSO) regression, 485,577 DNA methylation features were analyzed and selected from the t0 and tr datasets. A random forest classifier was developed using the t0 dataset and evaluated on the t2 dataset. Two models based on DNA methylation features were constructed and assessed using receiver operating characteristic (ROC) curves and Kaplan-Meier survival analyses.

Results: The ten-feature and four-feature models for predicting in-hospital mortality attained area under the curve (AUC) values of 0.78 and 0.72, respectively, with LASSO alpha values of 0.2 and 0.25. In contrast, clinical evaluation systems, including ICU scoring systems and the survival after venoarterial ECMO (SAVE) score, did not achieve statistical significance. Moreover, our models showed significant associations with in-hospital survival (p < 0.05, log-rank test).

Conclusions: This study identifies DNA methylation features in PBMCs as potent prognostic markers for ECMO-treated CS patients. Demonstrating significant predictive accuracy for in-hospital mortality, these markers offer a substantial advancement in patient stratification and might improve treatment outcomes.

Osteosarcoma (OS) is the most frequent primary malignant bone tumour, whose heterogeneity represents a major challenge for common antitumour therapies. Inflammatory cytokines are known to be necessary for OS progression. Therefore, to optimise therapy, it is important to discover reliable biomarkers by identifying the mechanism generating OS and investigating the inflammatory pathways that support the undifferentiated state. In this work, we highlight the differences of epigenetic activities of IL-1β and TNFα, and the susceptibility of TET-1 enzymatic inhibition, in tumour progression of three different OS cell lines. Investigating DNA methylation of IL-6 promoter and determining its expression, we found that TET enzymatic inhibition influences proliferation induced by inflammatory cytokines in OS cell lines. Moreover, Bobcat 339 treatment blocks IL-1β epigenetic action on IL-6 promoter, while only partially those of TNFα as well as inhibits IL-1β-dependent epithelial-mesenchymal transition (EMT) process, but only partially those of TNFα. In conclusion, this work highlights that IL-1β and TNFα have different effects on DNA demethylation in OS cell lines, making DNA methylation a potential biomarker of disease. Specifically, in IL-1β treatment, TET-1 inhibition completely blocks tumour progression, while in TNFα actions, it is only partially effective. Given that these two inflammatory pathways can be therapeutic targets for treating these tumours, knowledge of their distinct epigenetic behaviours can be useful for developing precise and specific therapeutic strategies for this disease.

Background: Controlled ovarian stimulation is a common skill of assisted reproductive technologies (ARTs). In the clinic, some females would undergo more than one controlled ovarian stimulation cycle. However, few studies have focused on the influence of multi-superovulation on oocytes and offspring.

Results: Here, we found that multi-superovulation disrupted the transcriptome of oocytes and that the differentially expressed genes (DEGs) were associated mainly with metabolism and fertilization. The disruption of mRNA degradation via poly (A) size and metabolism might be a reason for the reduced oocyte maturation rate induced by repeated superovulation. Multi-superovulation results in hypo-genomic methylation in oocytes. However, there was an increase in the methylation level of CGIs. The DMRs are not randomly distributed in genome elements. Genes with differentially methylated regions (DMRs) in promoters are enriched in metabolic pathways. With increasing of superovulation cycles, the glucose and insulin tolerance of offspring is also disturbed.

Conclusions: These results suggest that multi-superovulation has adverse effects on oocyte quality and offspring health.

Background: This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.

Methods and results: We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population.

Conclusions: Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.