ArticleNPJ Parkinson's disease2023
Identification of PLOD3 and LRRN3 as potential biomarkers for Parkinson's disease based on integrative analysis.
Article in NPJ Parkinson's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- Identification of TBXAS1 as a candidate biomarker and potential microglia-associated inflammatory regulator in Parkinson's disease.Scientific reports · 2026Article
- Screening of signaling pathways and hub genes in Guillain-Barré syndrome based on bioinformatics and machine learning.BMC neurology · 2026Article
- Integrating polygenic signals and single-cell multiomics identifies cell-type-specific regulomes critical for immune- and aging-related diseases.Nature aging · 2026Article
- Integrating Blood Biomarkers and Marine Brown Algae-Derived Inhibitors in Parkinson's Disease: A Multi-scale Approach from Interactomics to Quantum Mechanics.Molecular biotechnology · 2025Article
- Differential gene expression and immune profiling in Parkinson's disease: unveiling potential candidate biomarkers.BMC neurology · 2025Article
- Gene signatures and immune correlations in Parkinson's disease Braak stages.European journal of medical research · 2025Article
- Substantia nigra and blood gene signatures and biomarkers for Parkinson's disease from integrated multicenter microarray-based transcriptomic analyses.Frontiers in aging neuroscience · 2025Article
- Albendazole ameliorates aerobic glycolysis in myofibroblasts to reverse pulmonary fibrosis.Journal of translational medicine · 2024Article
- Analysis ofBiomedicines · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is one of the most prevalent movement disorders and its diagnosis relies heavily on the typical clinical manifestations in the late stages. This study aims to screen and identify biomarkers of PD for earlier intervention. We performed a differential analysis of postmortem brain transcriptome studies. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify biomarkers related to Braak stage. We found 58 genes with significantly different expression in both PD brain tissue and blood samples. PD gene signature and risk score model consisting of nine genes were constructed using least absolute shrinkage and selection operator regression (LASSO) and logistic regression. PLOD3 and LRRN3 in gene signature were identified to serve as key genes as well as potential risk factors in PD. Gene function enrichment analysis and evaluation of immune cell infiltration revealed that PLOD3 was implicated in suppression of cellular metabolic function and inflammatory cell infiltration, whereas LRRN3 exhibited an inverse trend. The cellular subpopulation expression of the PLOD3 and LRRN3 has significant distributional variability. The expression of PLOD3 was more enriched in inflammatory cell subpopulations, such as microglia, whereas LRRN3 was more enriched in neurons and oligodendrocyte progenitor cells clusters (OPC). Additionally, the expression of PLOD3 and LRRN3 in Qilu cohort was verified to be consistent with previous results. Collectively, we screened and identified the functions of PLOD3 and LRRN3 based the integrated study. The combined detection of PLOD3 and LRRN3 expression in blood samples can improve the early detection of PD.
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Registered trials
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