ArticleBMC medical genomics2020
Identification of contributing genes of Huntington's disease by machine learning.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review.Frontiers in neurology · 2024Pooled it
- KLF4 in Parkinson's Disease: Decoding the Molecular Puzzle of Neuroinflammation, Oxidative Stress, and Emerging Therapies.Current medical science · 2026Review
- Identifying time patterns in Huntington's disease trajectories using dynamic time warping-based clustering on multi-modal data.Scientific reports · 2025Article
- Machine learning identified novel players in lipid metabolism, endosomal trafficking, and iron metabolism of the ALS spinal cord.Scientific reports · 2025Article
- CMS121 Partially Attenuates Disease Progression in Mouse Models of Huntington's Disease.Molecular neurobiology · 2024Article
- Exploring Huntington's Disease Diagnosis via Artificial Intelligence Models: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2023Review
- A comprehensive analysis of gene expression profiling data in COVID-19 patients for discovery of specific and differential blood biomarker signatures.Scientific reports · 2023Article
- Leveraging Computational Intelligence Techniques for Diagnosing Degenerative Nerve Diseases: A Comprehensive Review, Open Challenges, and Future Research Directions.Diagnostics (Basel, Switzerland) · 2023Review
- A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease.Bioinformatics and biology insights · 2023Article
- Article
- Non-Cell Autonomous and Epigenetic Mechanisms of Huntington's Disease.International journal of molecular sciences · 2021Review
- Hypoxia-Inducible Factor (HIF) in Ischemic Stroke and Neurodegenerative Disease.Frontiers in cell and developmental biology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundHuntington's disease (HD) is an inherited disorder caused by the polyglutamine (poly-Q) mutations of the HTT gene results in neurodegeneration characterized by chorea, loss of coordination, cognitive decline. However, HD pathogenesis is still elusive. Despite the availability of a wide range of biological data, a comprehensive understanding of HD's mechanism from machine learning is so far unrealized, majorly due to the lack of needed data density.
methodsTo harness the knowledge of the HD pathogenesis from the expression profiles of postmortem prefrontal cortex samples of 157 HD and 157 controls, we used gene profiling ranking as the criteria to reduce the dimension to the order of magnitude of the sample size, followed by machine learning using the decision tree, rule induction, random forest, and generalized linear model.
resultsThese four Machine learning models identified 66 potential HD-contributing genes, with the cross-validated accuracy of 90.79 ± 4.57%, 89.49 ± 5.20%, 90.45 ± 4.24%, and 97.46 ± 3.26%, respectively. The identified genes enriched the gene ontology of transcriptional regulation, inflammatory response, neuron projection, and the cytoskeleton. Moreover, three genes in the cognitive, sensory, and perceptual systems were also identified.
conclusionsThe mutant HTT may interfere with both the expression and transport of these identified genes to promote the HD pathogenesis.
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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.