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GeroScience Jun 2024Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA...
Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA methylation levels have been found to serve as reliable biomarkers for biological aging. This study explores the relationship between various epigenetic biomarkers of aging and diabetes risk using longitudinal data. Data from the Swedish Adoption/Twin Study of Aging (SATSA) was collected from 1984 to 2014 and included 536 individuals with at least one epigenetic measurement. The following epigenetic biomarkers of aging were employed: DNAm PAI-1, DNAmTL, DunedinPACE, PCHorvath1, PCHorvath2, PCHannum, PCPhenoAge, and PCGrimAge. Firstly, longitudinal analysis of biomarker trajectories was done. Secondly, linear correlations between the biomarkers and time to diabetes were studied within individuals developing diabetes. Thirdly, Cox proportional hazards (PH) models were used to assess the associations between these biomarkers and time of diabetes diagnosis, with adjustments for chronological age, sex, education, smoking, blood glucose, and BMI. The longitudinal trajectories of the biomarkers revealed differences between individuals with and without diabetes. Smoothened average curves for DunedinPACE and DNAm PAI-1 were higher for individuals with diabetes around the age 60-70, compared to controls. Likewise, DunedinPACE and DNAm PAI-1 were higher closer to diabetes onset. However, no significant associations were found between the epigenetic biomarkers of aging and risk of diabetes in Cox PH models. Our findings suggest the potential value of developing epigenetic biomarkers specifically tailored to T2D, should we wish to model and explore the potential for predicting the disease.
PubMed: 38937415
DOI: 10.1007/s11357-024-01252-7 -
Journal of Neuro-oncology Jun 2024Diffuse midline gliomas (DMG) with H3K27 alterations (H3K27M-DMG) are a highly aggressive form of brain cancer. In rare cases, H3K27 mutations have been observed in...
PURPOSE
Diffuse midline gliomas (DMG) with H3K27 alterations (H3K27M-DMG) are a highly aggressive form of brain cancer. In rare cases, H3K27 mutations have been observed in diffuse non-midline gliomas (DNMG). It is currently unclear how these tumors should be classified. Herein, we analyze the characteristics of DNMG with H3K27M mutations.
METHODS
We reviewed the clinical, radiological and histological characteristics of all patients with an H3K27M mutated diffuse glioma diagnosed in our institution, between 2016 and 2023, to identify cases with a non-midline location. We then performed a molecular characterization (DNA methylation profiling, whole genome and transcriptome sequencing or targeted sequencing) of patients with an H3K27M-mutant DNMG and reviewed previously reported cases.
RESULTS
Among 51 patients (18 children and 33 adults) diagnosed with an H3K27M diffuse glioma, we identified two patients (4%) who had a non-midline location. Including our two patients, 39 patients were reported in the literature with an H3K27M-mutant DNMG. Tumors were most frequently located in the temporal lobe (48%), affected adolescents and adults, and were associated with a poor outcome (median overall survival was 10.3 months (0.1-84)). Median age at diagnosis was 19.1 years. Tumors frequently harbored TP53 mutations (74%), ATRX mutations (71%) and PDGFRA mutations or amplifications (44%). In DNA methylation analysis, H3K27M-mutant DNMG clustered within or close to the reference group of H3K27M-mutant DMG. Compared to their midline counterpart, non-midline gliomas with H3K27M mutations seemed more frequently associated with PDGFRA alterations.
CONCLUSION
DNMG with H3K27M mutations share many similarities with their midline counterpart, suggesting that they correspond to a rare anatomical presentation of these tumors. This is of paramount importance, as they may benefit from new therapeutic approaches such as ONC201.
PubMed: 38937309
DOI: 10.1007/s11060-024-04733-z -
Discover Oncology Jun 2024Acute myeloid leukemia, constituting a majority of leukemias, grapples with a 24% 5-year survival rate. Recent strides in research have unveiled fresh targets for drug...
BACKGROUND
Acute myeloid leukemia, constituting a majority of leukemias, grapples with a 24% 5-year survival rate. Recent strides in research have unveiled fresh targets for drug therapies. LIM-only, a pivotal transcription factor within LIM proteins, oversees cell development and is implicated in tumor formation. Among these critical LIM proteins, CSRP1, a Cysteine-rich protein, emerges as a significant player in various diseases. Despite its recognition as a potential prognostic factor and therapeutic target in various cancers, the specific link between CSRP1 and acute myeloid leukemia remains unexplored. Our previous work, identifying CSRP1 in a prognostic model for AML patients, instigates a dedicated exploration into the nuanced role of CSRP1 in acute myeloid leukemia.
METHODS
R tool was conducted to analyze the public data. qPCR was applied to evaluate the expression of CSRP1 mRNA for clinical samples and cell line. Unpaired t test, Wilcoxon Rank Sum test, KM curves, spearman correlation test and Pearson correlation test were included in this study.
RESULTS
CSRP1 displays notable expression variations between normal and tumor samples in acute myeloid leukemia (AML). It stands out as an independent prognostic factor for AML patients, showing correlations with clinical factors like age and cytogenetics risk. Additionally, CSRP1 correlates with immune-related pathways, immune cells, and immune checkpoints in AML. Furthermore, the alteration of CSRP1 mRNA levels is observed upon treatment with a DNMT1 inhibitor for THP1 cells.
CONCLUSION
The CSRP1 has potential as a novel prognostic factor and appears to influence the immune response in acute myeloid leukemia. Additionally, there is an observed association between CSRP1 and DNA methylation in acute myeloid leukemia.
PubMed: 38937285
DOI: 10.1007/s12672-024-01088-9 -
Cell Stress & Chaperones Jun 2024Epigenetic variations result from long-term adaptation to environmental factors. The Bos indicus (zebu) adapted to tropical conditions whereas Bos taurus to temperate...
Epigenetic variations result from long-term adaptation to environmental factors. The Bos indicus (zebu) adapted to tropical conditions whereas Bos taurus to temperate conditions, hence the native zebu cattle and its crossbred (B indicus X B taurus) show differences in responses to heat stress. The present study evaluated genome-wide DNA methylation profiles of these two breeds of cattle that may explain distinct heat stress responses. Physiological responses to heat stress and estimated values of Iberia heat tolerance coefficient (HTC) and Benezra's coefficient of adaptability (BCA) revealed better relative thermo-tolerance of Hariana compared to the Vrindavani cattle. Genome-wide DNA methylation patterns were different for Hariana and Vrindavani cattle. The comparison between breeds indicated presence of 4599 significant differentially methylated CpGs (DMC) with 756 hyper-methylated and 3845 hypo-methylated in Hariana compared to the Vrindavani cattle. Further, we found 79 genes that showed both differential methylation and differential expression that are involved cellular stress response functions. Differential methylations in the microRNA coding sequences also revealed their functions in heat stress responses. Taken together, epigenetic differences represent potential regulation of long-germ adaptation of Hariana (B indicus) cattle to the tropical environment and relative thermotolerance.
PubMed: 38936463
DOI: 10.1016/j.cstres.2024.06.005 -
Molecular Cell Jun 2024The bacterial world offers diverse strains for understanding medical and environmental processes and for engineering synthetic biological chassis. However, genetically...
The bacterial world offers diverse strains for understanding medical and environmental processes and for engineering synthetic biological chassis. However, genetically manipulating these strains has faced a long-standing bottleneck: how to efficiently transform DNA. Here, we report imitating methylation patterns rapidly in TXTL (IMPRINT), a generalized, rapid, and scalable approach based on cell-free transcription-translation (TXTL) to overcome DNA restriction, a prominent barrier to transformation. IMPRINT utilizes TXTL to express DNA methyltransferases from a bacterium's restriction-modification systems. The expressed methyltransferases then methylate DNA in vitro to match the bacterium's DNA methylation pattern, circumventing restriction and enhancing transformation. With IMPRINT, we efficiently multiplex methylation by diverse DNA methyltransferases and enhance plasmid transformation in gram-negative and gram-positive bacteria. We also develop a high-throughput pipeline that identifies the most consequential methyltransferases, and we apply IMPRINT to screen a ribosome-binding site library in a hard-to-transform Bifidobacterium. Overall, IMPRINT can enhance DNA transformation, enabling the use of sophisticated genetic manipulation tools across the bacterial world.
PubMed: 38936361
DOI: 10.1016/j.molcel.2024.06.003 -
Science (New York, N.Y.) Jun 2024Prion disease is caused by misfolding of the prion protein (PrP) into pathogenic self-propagating conformations, leading to rapid-onset dementia and death. However,...
Prion disease is caused by misfolding of the prion protein (PrP) into pathogenic self-propagating conformations, leading to rapid-onset dementia and death. However, elimination of endogenous PrP halts prion disease progression. In this study, we describe Coupled Histone tail for Autoinhibition Release of Methyltransferase (CHARM), a compact, enzyme-free epigenetic editor capable of silencing transcription through programmable DNA methylation. Using a histone H3 tail-Dnmt3l fusion, CHARM recruits and activates endogenous DNA methyltransferases, thereby reducing transgene size and cytotoxicity. When delivered to the mouse brain by systemic injection of adeno-associated virus (AAV), -targeted CHARM ablates PrP expression across the brain. Furthermore, we have temporally limited editor expression by implementing a kinetically tuned self-silencing approach. CHARM potentially represents a broadly applicable strategy to suppress pathogenic proteins, including those implicated in other neurodegenerative diseases.
Topics: Animals; Dependovirus; Mice; Brain; Prion Proteins; Gene Silencing; Epigenesis, Genetic; Histones; DNA Methylation; DNA (Cytosine-5-)-Methyltransferases; Prion Diseases; Humans; Transgenes
PubMed: 38935715
DOI: 10.1126/science.ado7082 -
Advanced Biology Jun 2024Population aging has increased the global prevalence of aging-related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease.... (Review)
Review
Population aging has increased the global prevalence of aging-related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence-associated β-galactosidase staining, telomere shortening, cell-cycle arrest, DNA methylation, and senescence-associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging-associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi-omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging-associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults.
PubMed: 38935557
DOI: 10.1002/adbi.202400079 -
Heliyon Jun 2024Aberrant epigenetic modifications, particularly DNA methylation, play a critical role in the pathogenesis and progression of human diseases. The current review aims to... (Review)
Review
Aberrant epigenetic modifications, particularly DNA methylation, play a critical role in the pathogenesis and progression of human diseases. The current review aims to reveal the role of aberrant DNA methylation in the pathogenesis and progression of diseases and to discuss the original data obtained from international research laboratories on this topic. In the review, we mainly summarize the studies exploring the role of aberrant DNA methylation as diagnostic and prognostic biomarkers in a broad range of human diseases, including monogenic epigenetics, autoimmunity, metabolic disorders, hematologic neoplasms, and solid tumors. The last section provides a general overview of the possibility of the DNA methylation machinery from the perspective of pharmaceutic approaches. In conclusion, the study of DNA methylation machinery is a phenomenal intersection that each of its ways can reveal the mysteries of various diseases, introduce new diagnostic and prognostic biomarkers, and propose a new patient-tailored therapeutic approach for diseases.
PubMed: 38933971
DOI: 10.1016/j.heliyon.2024.e32366 -
Frontiers in Genetics 2024Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA...
BACKGROUND
Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles.
METHODS
Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites.
RESULTS
We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction.
CONCLUSION
In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.
PubMed: 38933920
DOI: 10.3389/fgene.2024.1383852 -
Frontiers in Immunology 2024Targeted therapy for Sjögren's syndrome (SS) has become an important focus for clinicians. Multi-omics-wide Mendelian randomization (MR) analyses have provided new...
BACKGROUND
Targeted therapy for Sjögren's syndrome (SS) has become an important focus for clinicians. Multi-omics-wide Mendelian randomization (MR) analyses have provided new ideas for identifying potential drug targets.
METHODS
We conducted summary-data-based Mendelian randomization (SMR) analysis to evaluate therapeutic targets associated with SS by integrating DNA methylation, gene expression and protein quantitative trait loci (mQTL, eQTL, and pQTL, respectively). Genetic associations with SS were derived from the FinnGen study (discovery) and the GWAS catalog (replication). Colocalization analyses were employed to determine whether two potentially relevant phenotypes share the same genetic factors in a given region. Moreover, to delve deeper into potential regulation among DNA methylation, gene expression, and protein abundance, we conducted MR analysis to explore the causal relationship between candidate gene methylation and expression, as well as between gene expression and protein abundance. Drug prediction and molecular docking were further employed to validate the pharmacological activity of the candidate drug targets.
RESULTS
Upon integrating the multi-omics data, we identified three genes associated with SS risk: TNFAIP3, BTN3A1, and PLAU. The methylation of cg22068371 in BTN3A1 was positively associated with protein levels, consistent with the negative effect of cg22068371 methylation on the risk of SS. Additionally, positive correlations were observed between the gene methylation of PLAU (cg04939496) and expression, as well as between expression and protein levels. This consistency elucidates the promotional effects of PLAU on SS risk at the DNA methylation, gene expression, and protein levels. At the protein level, genetically predicted TNFAIP3 (OR 2.47, 95% CI 1.56-3.92) was positively associated with SS risk, while BTN3A1 (OR 2.96E-03, 95% CI 2.63E-04-3.33E-02) was negatively associated with SS risk. Molecular docking showed stable binding for candidate drugs and target proteins.
CONCLUSION
Our study reveals promising therapeutic targets for the treatment of SS, providing valuable insights into targeted therapy for SS. However, further validation through future experiments is warranted.
Topics: Humans; Sjogren's Syndrome; Mendelian Randomization Analysis; Quantitative Trait Loci; DNA Methylation; Genome-Wide Association Study; Molecular Docking Simulation; Genetic Predisposition to Disease; Molecular Targeted Therapy; Polymorphism, Single Nucleotide; Multiomics
PubMed: 38933282
DOI: 10.3389/fimmu.2024.1419363