The tissue specificity of DNA methylation refers to the significant differences in DNA methylation patterns in different tissues. This specificity regulates gene expression, thereby supporting the specific functions of each tissue and the maintenance of normal physiological activities. Abnormal tissue-specific patterns of DNA methylation are closely related to age-related diseases. This abnormal methylation pattern affects the regulation of gene expression, which may lead to changes in cell function and promote the occurrence of pathological conditions. By analyzing the differences in these methylation patterns, key CpG sites for disease diagnosis can be effectively screened. The main goal of this paper is to use the characteristics associated with tissue-specific abnormal expression and disease to construct an age-related disease diagnosis model. First, we combined chi-square tests and logistic regression to identify tissue-specific and disease-specific CpG sites, laying the foundation for accurate medical diagnosis, and verified the biological relevance of these CpG sites through enrichment analysis. Then we used the Transformer model to fit these CpG sites and realized the automatic diagnosis of age-related diseases. Our work proves that the tissue specificity of DNA methylation has the potential to diagnose age-related diseases, and proves the scientific nature of our proposed diagnostic method from a biological perspective.
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http://dx.doi.org/10.3390/ijms26020452 | DOI Listing |
Mol Plant
January 2025
State Key Laboratory of Wheat Improvement, School of Advanced Agricultural Sciences, Peking University, Beijing 100871, China; Beijing Life Science Academy, Beijing 102299, China. Electronic address:
It has been hypothesized that DNA damage has the potential to induce DNA hypermethylation, contributing to carcinogenesis in mammals. However, there is no sufficient evidence to support that DNA damage can cause genome-wide DNA hypermethylation. Here, we demonstrated that DNA single-strand breaks with 3'-blocked ends (DNA 3'-blocks) can not only reinforce DNA methylation at normally methylated loci but also can induce DNA methylation at normally nonmethylated loci in plants.
View Article and Find Full Text PDFClin Epigenetics
January 2025
Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFSci Rep
January 2025
The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Road, Zhengzhou, 450052, Henan, China.
Netrin-1 (NTN1) is a laminin-related secreted protein involved in axon guidance and cell migration. Previous research has established a significant connection between NTN1 and nervous system development. In recent years, mounting evidence indicates that NTN1 also plays a crucial role in tumorigenesis and tumor progression.
View Article and Find Full Text PDFNat Commun
January 2025
Division of Evolutionary Biology, Faculty of Biology, LMU Munich, Planegg-Martinsried, Germany.
The evolutionary impact of epigenetic variation depends on its transgenerational stability and source - whether genetically determined, environmentally induced, or due to spontaneous, genotype-independent mutations. Here, we evaluate current approaches for investigating an independent role of epigenetics in evolution, pinpointing methodological challenges. We further identify opportunities arising from integrating epigenetic data with population genetic analyses in natural populations.
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