ArticleScientific reports2021
Dementia subtype prediction models constructed by penalized regression methods for multiclass classification using serum microRNA expression data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- The role of microRNAs in understanding sex-based differences in Alzheimer's disease.Biology of sex differences · 2024Pooled it
- Article
- Plasma multi-miRNA models classify Alzheimer's, Parkinson's, and Lewy body dementia.Frontiers in aging neuroscience · 2026Article
- Review
- Article
- Exploring the Regulatory Landscape of Dementia: Insights from Non-Coding RNAs.International journal of molecular sciences · 2024Review
- Classification performance assessment for imbalanced multiclass data.Scientific reports · 2024Article
- Biomarker profiling to determine clinical impact of microRNAs in cognitive disorders.Scientific reports · 2024Article
- Identification of prognostic RNA editing profiles for clear cell renal carcinoma.Frontiers in medicine · 2024Article
- Alcohol Use Disorder and Dementia: A Review.Alcohol research : current reviews · 2024Review
- Article
- Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.Frontiers in genetics · 2022Article
- Machine learning uncovers novel sex-specific dementia biomarkers linked to autism and eye diseases.Journal of Alzheimer's disease reportsArticle
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There are many subtypes of dementia, and identification of diagnostic biomarkers that are minimally-invasive, low-cost, and efficient is desired. Circulating microRNAs (miRNAs) have recently gained attention as easily accessible and non-invasive biomarkers. We conducted a comprehensive miRNA expression analysis of serum samples from 1348 Japanese dementia patients, composed of four subtypes-Alzheimer's disease (AD), vascular dementia, dementia with Lewy bodies (DLB), and normal pressure hydrocephalus-and 246 control subjects. We used this data to construct dementia subtype prediction models based on penalized regression models with the multiclass classification. We constructed a final prediction model using 46 miRNAs, which classified dementia patients from an independent validation set into four subtypes of dementia. Network analysis of miRNA target genes revealed important hub genes, SRC and CHD3, associated with the AD pathogenesis. Moreover, MCU and CASP3, which are known to be associated with DLB pathogenesis, were identified from our DLB-specific target genes. Our study demonstrates the potential of blood-based biomarkers for use in dementia-subtype prediction models. We believe that further investigation using larger sample sizes will contribute to the accurate classification of subtypes of dementia.
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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.