ArticleNature communications2021
A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer's disease.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.
- A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis.International journal of molecular sciences · 2024Pooled it
- Hybrid CNN and multi-head attention model for analyzing epigenetic mechanisms and gene expression across fungal phylogenetic distances.iScience · 2026Article
- A universal deep learning framework for empowering nanopore identification by reinforcing temporal signals.Nature communications · 2026Article
- A hybrid GPR framework with feature selection for enhanced prediction and explainability of subgrade soil strength.Scientific reports · 2026Article
- MethConvTransformer: A Deep Learning Framework for Cross-Tissue Alzheimer's Disease Detection.ArXiv · 2026Article
- Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.Scientific reports · 2025Article
- DNA Methylation in Alzheimer's Disease.Current topics in behavioral neurosciences · 2025Review
- Decoding the Methylome: Insights into the Epigenetic Regulation of Polycystic Ovarian Syndrome through Mitochondrial DNA Methylation.Current genomics · 2025Review
- AD-Diff: enhancing Alzheimer's disease prediction accuracy through multimodal fusion.Frontiers in computational neuroscience · 2025Article
- Identifying Alzheimer's disease-associated genes using PhenoGeneRanker.bioRxiv : the preprint server for biology · 2024Article
- An explainable machine learning approach for Alzheimer's disease classification.Scientific reports · 2024Article
- Pleiotropic functions of TAO kinases and their dysregulation in neurological disorders.Science signaling · 2024Review
- Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Designing Epigenome Editors: Considerations of Biochemical and Locus Specificities.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The Potential for Artificial Intelligence Applied to Epigenetics.Mayo Clinic proceedings. Digital health · 2023Article
- Artificial intelligence for dementia genetics and omics.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023Review
- SpeCamX: mobile app that turns unmodified smartphones into multispectral imagers.Biomedical optics express · 2023Article
- Role of TET1-mediated epigenetic modulation in Alzheimer's disease.Neurobiology of disease · 2023Article
- Genome-wide association studies: utility and limitations for research in physiology.The Journal of physiology · 2023Article
- Epigenomic signatures reveal mechanistic clues and predictive markers for autism spectrum disorder.Molecular psychiatry · 2023Review
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 2 countries.
Funding
Abstract
Alzheimer's disease (AD) is influenced by both genetic and environmental factors; thus, brain epigenomic alterations may provide insights into AD pathogenesis. Multiple array-based Epigenome-Wide Association Studies (EWASs) have identified robust brain methylation changes in AD; however, array-based assays only test about 2% of all CpG sites in the genome. Here, we develop EWASplus, a computational method that uses a supervised machine learning strategy to extend EWAS coverage to the entire genome. Application to six AD-related traits predicts hundreds of new significant brain CpGs associated with AD, some of which are further validated experimentally. EWASplus also performs well on data collected from independent cohorts and different brain regions. Genes found near top EWASplus loci are enriched for kinases and for genes with evidence for physical interactions with known AD genes. In this work, we show that EWASplus implicates additional epigenetic loci for AD that are not found using array-based AD EWASs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.