ArticleBioscience reports2020
Immune-associated biomarkers for early diagnosis of Parkinson's disease based on hematological lncRNA-mRNA co-expression.
Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Single-cell analysis of the peripheral immune landscape in Parkinson's disease: insights into dendritic cell and CD4+ T-cell transcriptomics.NPJ Parkinson's disease · 2026Article
- A novel integrative multimodal classifier to enhance the diagnosis of Parkinson's disease.Briefings in bioinformatics · 2025Article
- Targeting Shp2 as a therapeutic strategy for neurodegenerative diseases.Translational psychiatry · 2025Review
- Extracellular vesicles as carriers of mRNA: Opportunities and challenges in diagnosis and treatment.Theranostics · 2024Review
- Identification and functional prediction of long non-coding RNA and mRNA related to connective tissue disease-associated interstitial lung diseases.Rheumatology and immunology research · 2023Article
- Comprehensive Characterization of Immune Landscape Based on Tumor Microenvironment for Oral Squamous Cell Carcinoma Prognosis.Vaccines · 2022Article
- Dysregulated lncRNAs are Involved in the Progress of Sepsis by Constructing Regulatory Networks in Whole Blood Cells.Frontiers in pharmacology · 2021Article
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Authors and funding
7 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early stage diagnosis of Parkinson's disease (PD) is challenging without significant motor symptoms. The identification of effective molecular biomarkers as a hematological indication of PD may help improve the diagnostic timeliness and accuracy. In this paper, we analyzed and compared the blood samples of PD and control (CTR) patients to identify the disease-related changes and determine the putative biomarkers for PD diagnosis. Based on the RNA sequencing analysis, differentially expressed genes (DEGs) were identified, and the co-expression network of DEGs was constructed using the weighted correlation network analysis (WGCNA). The analysis leads to the identification of 87 genes that were exclusively regulated in the PD group, whereas 66 genes were significantly increased and 21 genes were significantly decreased in contrast to the control group. The results indicate that the core lncRNA-mRNA co-expression network greatly changes the immune response in PD patients. Specifically, the results showed that PWAR6, LINC00861, AC83843.1, IRF family, IFIT family and CaMK4 may play important roles in the immune system of PD. Based on the findings from this the present study, future research aims at identify novel therapeutic strategies for PD.
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