ArticleClinical epigenetics2019
Identification of potential blood biomarkers for Parkinson's disease by gene expression and DNA methylation data integration analysis.
Article in Clinical epigenetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed, 73 citations in OpenAlex.
- Epigenetic changes associated with the progression of prion disease in Syrian hamsters (Prion · 2026Article
- Study of blood linear RNA nominates CD55 and DLD as early-stage biomarkers for Parkinson's disease.Brain : a journal of neurology · 2026Article
- Advances in biomarkers for Parkinson's disease: from molecular pathology to precision diagnostics.Journal of Zhejiang University. Science. B · 2026Review
- Inherent variability limits clinical utility of reproducible Parkinson's transcriptomics signatures.NPJ Parkinson's disease · 2025Article
- Epigenetic Changes Associated with the Progression of Prion Disease in Syrian Hamsters (Mesocricetus auratus).Research square · 2025Article
- Pre-existing DNA methylation signatures in the prefrontal cortex of alcohol-naïve nonhuman primates define neural vulnerability for future risky ethanol consumption.Neurobiology of disease · 2025Article
- Integration of Methylation and Gene Expression Deciphered Candidate Biomarkers DAB2IP and SMYD3 in Delayed Encephalopathy After Carbon Monoxide Poisoning.CNS neuroscience & therapeutics · 2025Article
- The Promise of Epigenetic Editing for Treating Brain Disorders.Sub-cellular biochemistry · 2025Review
- NBR and GBA Gene Methylation Levels in the Peripheral Blood of Parkinson's Disease Patients.Journal of movement disorders · 2024Article
- DNA methylation clocks for estimating biological age in Chinese cohorts.Protein & cell · 2024Article
- Vault RNAs (vtRNAs): Rediscovered non-coding RNAs with diverse physiological and pathological activities.Genes & diseases · 2024Review
- Transcriptome-based biomarker prediction for Parkinson's disease using genome-scale metabolic modeling.Scientific reports · 2024Article
- Mitochondrial stress-induced H4K12 hyperacetylation dysregulates transcription in Parkinson's disease.Frontiers in cellular neuroscience · 2024Article
- Emerging perspectives on precision therapy for Parkinson's disease: multidimensional evidence leading to a new breakthrough in personalized medicine.Frontiers in aging neuroscience · 2024Review
- Pan-precancer and cancer DNA methylation profiles revealed significant tissue specificity of interrupted biological processes in tumorigenesis.Epigenetics · 2023Article
- Blood biomarker-based classification study for neurodegenerative diseases.Scientific reports · 2023Article
- Article
- Nomogram for Early Prediction of Parkinson's Disease Based on microRNA Profiles and Clinical Variables.Journal of Parkinson's disease · 2023Article
- DNA Methylation Alterations in Fractionally Irradiated Rats and Breast Cancer Patients Receiving Radiotherapy.International journal of molecular sciences · 2022Article
- Epigenetic Changes in Prion and Prion-like Neurodegenerative Diseases: Recent Advances, Potential as Biomarkers, and Future Perspectives.International journal of molecular sciences · 2022Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBlood-based gene expression or epigenetic biomarkers of Parkinson's disease (PD) are highly desirable. However, accuracy and specificity need to be improved, and methods for the integration of gene expression with epigenetic data need to be developed in order to make this feasible.
methodsWhole blood gene expression data and DNA methylation data were downloaded from Gene Expression Omnibus (GEO) database. A linear model was used to identify significantly differentially expressed genes (DEGs) and differentially methylated genes (DMGs) according to specific gene regions 5'-C-phosphate-G-3' (CpGs) or all gene regions CpGs in PD. Gene set enrichment analysis was then applied to DEGs and DMGs. Subsequently, data integration analysis was performed to identify robust PD-associated blood biomarkers. Finally, the random forest algorithm and a leave-one-out cross validation method were performed to construct classifiers based on gene expression data integrated with methylation data.
resultsEighty-five (85) significantly hypo-methylated and upregulated genes in PD patients compared to healthy controls were identified. The dominant hypo-methylated regions of these genes were significantly different. Some genes had a single dominant hypo-methylated region, while others had multiple dominant hypo-methylated regions. One gene expression classifier and two gene methylation classifiers based on all or dominant methylation-altered region CpGs were constructed. All have a good prediction power for PD.
conclusionsGene expression and methylation data integration analysis identified a blood-based 53-gene signature, which could be applied as a biomarker for PD.
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