ArticleGenomics, proteomics & bioinformatics2019
Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs.
Article in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 82 citations in OpenAlex.
- Rethinking Alzheimer's: novel miRNAs illuminate a disease beyond the brain.Molecular psychiatry · 2026Pooled it
- Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer's disease by meta-analysis and adaptive boosting ensemble learning.Alzheimer's research & therapy · 2021Pooled it
- Development of a serum-based microRNA panel for Alzheimer's disease diagnosis.Journal of translational internal medicine · 2026Article
- Extracellular vesicle and particle biomarkers in cancer: a machine learning blueprint for liquid biopsy.Journal of nanobiotechnology · 2026Review
- Plasma multi-miRNA models classify Alzheimer's, Parkinson's, and Lewy body dementia.Frontiers in aging neuroscience · 2026Article
- AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.Briefings in bioinformatics · 2024Article
- Non-fatal outcomes of COVID-19 disease in pediatric organ transplantation associates with down-regulation of senescence pathways.Scientific reports · 2024Article
- Death-associated protein kinase 1 as a therapeutic target for Alzheimer's disease.Translational neurodegeneration · 2024Review
- Blood-Based Transcriptomic Biomarkers Are Predictive of Neurodegeneration Rather Than Alzheimer's Disease.International journal of molecular sciences · 2023Article
- Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson's disease.Scientific reports · 2023Article
- Salivary biomarkers: novel noninvasive tools to diagnose chronic inflammation.International journal of oral science · 2023Review
- Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning.Sensors (Basel, Switzerland) · 2023Review
- Exploiting machine learning models to identify novel Alzheimer's disease biomarkers and potential targets.Scientific reports · 2023Review
- Exosomal miR-532-5p induced by long-term exercise rescues blood-brain barrier function in 5XFAD mice via downregulation of EPHA4.Aging cell · 2023Article
- Common microRNA regulated pathways in Alzheimer's and Parkinson's disease.Frontiers in neuroscience · 2023Article
- Identification of miRNAs in extracellular vesicles as potential diagnostic markers for pediatric epilepsy and drug-resistant epilepsy via bioinformatics analysis.Frontiers in pediatrics · 2023Article
- MicroRNA: A Linking between Astrocyte Dysfunction, Mild Cognitive Impairment, and Neurodegenerative Diseases.Life (Basel, Switzerland) · 2022Review
- Differential microRNA expression analyses across two brain regions in Alzheimer's disease.Translational psychiatry · 2022Article
- Advances in the development of new biomarkers for Alzheimer's disease.Translational neurodegeneration · 2022Review
- Review
Corrections and comments
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Authors and funding
18 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previously, we published high-throughput sequencing based microRNA (miRNA) signatures in Alzheimer's disease (AD) patients in the United States (US) and Germany. Here, we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR. We computed models to assess the relation between miRNA expression and phenotypes, gender, age, or disease severity (Mini-Mental State Examination; MMSE). Of the 21 miRNAs, expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts. 18 miRNAs were significantly correlated with neurodegeneration (Benjamini-Hochberg adjusted P < 0.05) with highest significance for miR-532-5p (Benjamini-Hochberg adjusted P = 4.8 × 10
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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.