ArticleScientific reports2021
Non-invasive diagnostic tool for Parkinson's disease by sebum RNA profile with machine learning.
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 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 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
- Article
- Review
- Dermatological Manifestations and Sebum Composition in Parkinson's Disease.Dermatology practical & conceptual · 2025Review
- Non-invasive SARS-CoV-2 RNA detection and human transcriptome analysis using skin surface lipids.Scientific reports · 2024Article
- Comprehensive data for studying serum exosome microRNA transcriptome in Parkinson's disease patients.Scientific data · 2024Article
- Impact of Dupilumab on Skin Surface Lipid-RNA Profile in Severe Asthmatic Patients.Current issues in molecular biology · 2024Article
- A Systematic Review of Extracellular Matrix-Related Alterations in Parkinson's Disease.Brain sciences · 2024Review
- A fast and non-invasive artificial intelligence olfactory-like system that aids diagnosis of Parkinson's disease.European journal of neurology · 2024Article
- Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative Model: Protocol for a Cross-sectional Study.JMIR research protocols · 2023Article
- Interpretable Machine Learning on Metabolomics Data Reveals Biomarkers for Parkinson's Disease.ACS central science · 2023Article
- Non-invasive transcriptomic analysis using mRNAs in skin surface lipids obtained from children with mild-to-moderate atopic dermatitis.Journal of the European Academy of Dermatology and Venereology : JEADV · 2022Article
- Multi-modality machine learning predicting Parkinson's disease.NPJ Parkinson's disease · 2022Article
- Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids.Communications biology · 2022Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disease presenting with motor and non-motor symptoms, including skin disorders (seborrheic dermatitis, bullous pemphigoid, and rosacea), skin pathological changes (decreased nerve endings and alpha-synuclein deposition), and metabolic changes of sebum. Recently, a transcriptome method using RNA in skin surface lipids (SSL-RNAs) which can be obtained non-invasively with an oil-blotting film was reported as a novel analytic method of sebum. Here we report transcriptome analyses using SSL-RNAs and the potential of these expression profiles with machine learning as diagnostic biomarkers for PD in double cohorts (PD [n = 15, 50], controls [n = 15, 50]). Differential expression analysis between the patients with PD and healthy controls identified more than 100 differentially expressed genes in the two cohorts. In each cohort, several genes related to oxidative phosphorylation were upregulated, and gene ontology analysis using differentially expressed genes revealed functional processes associated with PD. Furthermore, machine learning using the expression information obtained from the SSL-RNAs was able to efficiently discriminate patients with PD from healthy controls, with an area under the receiver operating characteristic curve of 0.806. This non-invasive gene expression profile of SSL-RNAs may contribute to early PD diagnosis based on the neurodegeneration background.
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