ArticleGenes2022
A Machine Learning Approach to Parkinson's Disease Blood Transcriptomics.
Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis.International journal of molecular sciences · 2024Pooled it
- Insights Into the Role of Platelet Factor 4 in Neurodegenerative Diseases.CNS neuroscience & therapeutics · 2026Review
- Semi-supervised ensemble learning with interval type-2 fuzzy-rough sets for Parkinson's disease prediction from multi-omics.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Article
- Integrative multi-omics and network-based machine learning for early diagnosis of Parkinson's disease.PloS one · 2026Article
- Inherent variability limits clinical utility of reproducible Parkinson's transcriptomics signatures.NPJ Parkinson's disease · 2025Article
- Neural networks reveal novel gene signatures in Parkinson disease from single-nuclei transcriptomes.NPJ Parkinson's disease · 2025Article
- Utility of the continuous spectrum formed by pathological states in characterizing disease properties.NPJ systems biology and applications · 2025Article
- Multi-omics machine learning classifier and blood transcriptomic signature of Parkinson's disease.Research square · 2025Article
- Transcriptomics profiling of Parkinson's disease progression subtypes reveals distinctive patterns of gene expression.Journal of central nervous system disease · 2025Article
- A Systematic Review of Extracellular Matrix-Related Alterations in Parkinson's Disease.Brain sciences · 2024Review
- Federated learning for multi-omics: A performance evaluation in Parkinson's disease.Patterns (New York, N.Y.) · 2024Article
- Federated Learning for multi-omics: a performance evaluation in Parkinson's disease.bioRxiv : the preprint server for biology · 2024Article
- Blood transcriptomic signatures associated with molecular changes in the brain and clinical outcomes in Parkinson's disease.Nature communications · 2023Article
- DNA Methylation Changes in Autologous Hematopoietic Stem Cell Transplant Patients.Biological research for nursing · 2023Article
- Article
- Machine Learning Analysis of RNA-seq Data for Diagnostic and Prognostic Prediction of Colon Cancer.Sensors (Basel, Switzerland) · 2023Article
- Machine learning within the Parkinson's progression markers initiative: Review of the current state of affairs.Frontiers in aging neuroscience · 2023Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increased incidence and the significant health burden associated with Parkinson's disease (PD) have stimulated substantial research efforts towards the identification of effective treatments and diagnostic procedures. Despite technological advancements, a cure is still not available and PD is often diagnosed a long time after onset when irreversible damage has already occurred. Blood transcriptomics represents a potentially disruptive technology for the early diagnosis of PD. We used transcriptome data from the PPMI study, a large cohort study with early PD subjects and age matched controls (HC), to perform the classification of PD vs. HC in around 550 samples. Using a nested feature selection procedure based on Random Forests and XGBoost we reached an AUC of 72% and found 493 candidate genes. We further discussed the importance of the selected genes through a functional analysis based on GOs and KEGG pathways.
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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.