ArticleJournal of translational medicine2023
DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data.
Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Exploring the causal effect of genetically predicted blood and cerebrospinal fluid metabolites and metabolic pathways on intracranial aneurysm.The Journal of international medical research · 2026Pooled it
- Differential DNA methylation associated with delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a systematic review.Neurosurgical review · 2024Pooled it
- Systematic Review of Radiomics and Artificial Intelligence in Intracranial Aneurysm Management.Journal of neuroimaging : official journal of the American Society of NeuroimagingPooled it
- Investigating the mechanisms of PhIP-induced colorectal cancer through network toxicology, machine learning, and molecular dynamics simulation.Translational cancer research · 2026Article
- Targeting SLK protects against cerebral ischemia-reperfusion injury by regulating USP8-mediated HIF-1α stabilization and RhoA/ROCK activation.Cellular & molecular biology letters · 2026Article
- Mechanistic Insights into PET-MPs-Aggravated Ischemic Stroke via Integrated Computational-Experimental Approaches.Environmental science & technology · 2026Article
- MICA and CYTH4 as immunological biomarkers of intracranial aneurysm: a study integrating RNA sequencing, single-cell sequencing and Mendelian randomization.Functional & integrative genomics · 2026Article
- Macrophage polarization-related genes with potential causal roles in osteoporosis: a multi-omics Mendelian randomization study.Journal of orthopaedic surgery and research · 2026Article
- Machine Learning-Based Identification of Immune Inflammation-Related Genes as Shared Potential Diagnostic Biomarkers in Autism Spectrum Disorder and Atopic Dermatitis.Biomedicines · 2026Article
- DNA Methylation-Regulated ZDHHC24 Exacerbates the Risk of Intracranial Aneurysms.Brain and behavior · 2026Article
- Multiomics genetic insights into potential molecular targets for intracranial aneurysm.Stroke and vascular neurology · 2026Article
- Cleaning, Chasing and Calming: Promising Paradigms of Senotherapy in Aging-Related Diseases.International journal of biological sciences · 2026Review
- Machine learning and multi-omics technologies for precision cardiovascular medicine: advancing diagnosis, risk prediction, and therapeutic guidance.Frontiers in cardiovascular medicine · 2026Review
- Identification of key biomarkers for myocardial infarction by multi-omics analysis and machine learning.Frontiers in immunology · 2026Article
- Article
- Epigenetic mechanisms in aneurysm formation, growth, and rupture: A systematic review.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2025Review
- Explainable machine learning-driven models for predicting Parkinson's disease and its prognosis: obesity patterns associations and models development using NHANES 1999-2018 data.Lipids in health and disease · 2025Article
- Investigating the potential of oxidative stress-related gene as predictive markers in idiopathic pulmonary fibrosis.Scientific reports · 2025Article
- Article
- Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions.
methodsWe employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA.
resultsWe identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition.
conclusionThese insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis.
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