AIMC Topic: CpG Islands
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Circulating epigenetic signatures classifying brain insulin resistance in humans.
Science translational medicine
Aug 6, 2025
Brain insulin action plays an important role in metabolic and cognitive health, but there is no biomarker available to assess brain insulin resistance in humans. Here, we developed a machine learning framework based on blood DNA methylation profiles ...
Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia.
Nature communications
Jul 29, 2025
Despite the critical role of DNA methylation, clinical implementations harnessing its promise have not been described in acute myeloid leukemia. Utilizing DNA methylation from 3314 leukemia patient samples across 11 harmonized cohorts, we describe th...
Exploring potential methylation markers for ovarian cancer from cervical scraping samples.
Human genomics
May 17, 2025
BACKGROUND: Ovarian cancer has the highest mortality rate among gynecological cancers, making early detection crucial, as the five-year survival rate drops from 92% with early-stage diagnosis compared to 31% with late-stage diagnosis. Current diagnos...
Epigenome-wide association study identifies a specific panel of DNA methylation signatures for antenatal and postpartum depressive symptoms.
Journal of affective disorders
Apr 24, 2025
Depression during pregnancy and postpartum poses significant risks to both maternal and child well-being. The underlying biological mechanisms are unclear, but epigenetic variation could be exploited as a plausible candidate for early detection. We i...
Genome-wide methylome modeling via generative AI incorporating long- and short-range interactions.
Science advances
Apr 11, 2025
Using millions of methylation segments, we developed DiffuCpG, a generative artificial intelligence (AI) diffusion model designed to solve the critical challenge of missing data in high-throughput methylation technologies. DiffuCpG goes beyond conven...
Deep learning imputes DNA methylation states in single cells and enhances the detection of epigenetic alterations in schizophrenia.
Cell genomics
Feb 21, 2025
DNA methylation (DNAm) is a key epigenetic mark with essential roles in gene regulation, mammalian development, and human diseases. Single-cell technologies enable profiling DNAm at cytosines in individual cells, but they often suffer from low covera...
Explainable artificial intelligence of DNA methylation-based brain tumor diagnostics.
Nature communications
Feb 20, 2025
We have recently developed a machine learning classifier that enables fast, accurate, and affordable classification of brain tumors based on genome-wide DNA methylation profiles that is widely employed in the clinic. Neuro-oncology research would ben...
Identification of a novel hypermethylation marker, ZSCAN18, and construction of a diagnostic model in cervical cancer.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Feb 19, 2025
PURPOSE: Cervical cancer (CC), a common female malignancy, has been linked to alterations in DNA methylation. This study employed an integrated "dry-wet lab" strategy combining bioinformatics, machine learning, and experimental validation to identify...
Identification of 17 novel epigenetic biomarkers associated with anxiety disorders using differential methylation analysis followed by machine learning-based validation.
Clinical epigenetics
Feb 17, 2025
BACKGROUND: The changes in DNA methylation patterns may reflect both physical and mental well-being, the latter being a relatively unexplored avenue in terms of clinical utility for psychiatric disorders. In this study, our objective was to identify ...
Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders.
Science advances
Jan 1, 2025
DNA methylation (DNAm) is essential for brain development and function and potentially mediates the effects of genetic risk variants underlying brain disorders. We present INTERACT, a transformer-based deep learning model to predict regulatory varian...
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