Long non-coding RNA UCA1 regulates MPP+-induced neuronal damage through the miR-671-5p/KPNA4 pathway in SK-N-SH cells

Integrative analysis of plasma and substantia nigra in Parkinson's disease: unraveling biomarkers and insights from the lncRNA-miRNA-mRNA ceRNA network

Introduction

Parkinson's disease (PD) is a rapidly growing neurological disorder characterized by diverse movement symptoms. However, the underlying causes have not been clearly identified, and accurate diagnosis is challenging. This study aimed to identify potential biomarkers suitable for PD diagnosis and present an integrative perspective on the disease.

Methods

We screened the GSE7621, GSE8397-GPL96, GSE8397-GPL97, GSE20163, and GSE20164 datasets in the NCBI GEO database to identify differentially expressed (DE) mRNAs in the substantia nigra (SN). We also screened the GSE160299 dataset from the NCBI GEO database to identify DE lncRNAs and miRNAs in plasma. We then constructed 2 lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory networks based on the ceRNA hypothesis. To understand the biological function, we performed Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses for each ceRNA network. The receiver operating characteristic analyses (ROC) was used to assess ceRNA results.

Results

We identified 7 upregulated and 29 downregulated mRNAs as common DE mRNAs in the 5 SN datasets. In the blood dataset, we identified 31 DE miRNAs (9 upregulated and 22 downregulated) and 332 DE lncRNAs (69 upregulated and 263 downregulated). Based on the determined interactions, 5 genes (P2RX7, HSPA1, SLCO4A1, RAD52, and SIRT4) appeared to be upregulated as a result of 10 lncRNAs sponging 4 miRNAs (miR-411, miR-1193, miR-301b, and miR-514a-2/3). Competing with 9 genes (ANK1, CBLN1, RGS4, SLC6A3, SYNGR3, VSNL1, DDC, KCNJ6, and SV2C) for miR-671, a total of 26 lncRNAs seemed to function as ceRNAs, influencing genes to be downregulated.

Discussion

In this study, we successfully constructed 2 novel ceRNA regulatory networks in patients with PD, including 36 lncRNAs, 5 miRNAs, and 14 mRNAs. Our results suggest that these plasma lncRNAs are involved in the pathogenesis of PD by sponging miRNAs and regulating gene expression in the SN of the brain. We propose that the upregulated and downregulated lncRNA-mediated ceRNA networks represent mechanisms of neuroinflammation and dopamine neurotransmission, respectively. Our ceRNA network, which was associated with PD, suggests the potential use of DE miRNAs and lncRNAs as body fluid diagnostic biomarkers. These findings provide an integrated view of the mechanisms underlying gene regulation and interactions in PD.

Neuronal dysfunction and gene modulation by non-coding RNA in Parkinson's disease and synucleinopathies

Over the last few decades, emerging evidence suggests that non-coding RNAs (ncRNAs) including long-non-coding RNA (lncRNA), microRNA (miRNA) and circular-RNA (circRNA) contribute to the molecular events underlying progressive neuronal degeneration, and a plethora of ncRNAs have been identified significantly misregulated in many neurodegenerative diseases, including Parkinson's disease and synucleinopathy. Although a direct link between neuropathology and causative candidates has not been clearly established in many cases, the contribution of ncRNAs to the molecular processes leading to cellular dysfunction observed in neurodegenerative diseases has been addressed, suggesting that they may play a role in the pathophysiology of these diseases. Aim of the present Review is to overview and discuss recent literature focused on the role of RNA-based mechanisms involved in different aspects of neuronal pathology in Parkinson's disease and synucleinopathy models.

Identification of biomarkers associated with immune scores in diabetic retinopathy

Background

Diabetic retinopathy (DR) causes irreversible visual impairment in diabetes mellitus (DM) patients. Immunity played a crucial role in DR. Nevertheless, the triggering mechanism of DR was not yet thorough enough. Herein, we aim to identify the immune-associated genes as biomarkers associated with immune scores that can distinguish early DR from DM without DR.

Methods

In this study, total RNA of peripheral blood mononuclear cell (PBMC) samples from 15 non-proliferative DR patients and 15 DM patients without DR were collected and the transcriptome sequencing data were extracted. Firstly, the target genes were obtained by intersecting the differentially expressed genes (DEGs), which were screened by "limma", and the module genes (related to immune scores), which were screened by "WGCNA". In order to screen for the crucial genes, three machine learning algorithms were implemented, and a receiver operating characteristic (ROC) curve was used to obtain the diagnostic genes. Moreover, the gene set enrichment analysis (GSEA) was performed to understand the function of diagnostic genes, and analysis of the proportions of immune cells and their association with diagnostic genes was performed to analyze the pathogenesis of DR. Furthermore, the regulatory network of TF-mRNA-miRNA was built to reveal the possible regulation of diagnostic genes. Finally, the quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the mRNA level of diagnostic genes.

Results

A total of three immune-associated diagnostic genes, namely, FAM209B, POM121L1P, and PTGES, were obtained, and their expression was increased in PBMC samples of DR, and qRT-PCR results confirmed these results. Moreover, the functions of these genes were associated with immune response. The expression of POM121L1P and PTGES was significantly negatively associated with naive B cells, and the expression of FAM209B was significantly negatively associated with immature dendritic cells. Moreover, ESR1 could regulate both FAM209B and PTGES.

Conclusion

This study identified three immune-associated diagnostic genes, FAM209B, POM121L1P, and PTGES, as biomarkers associated with immune scores in DR for the first time. This finding might proffer a novel perspective of the triggering mechanism of DR, and help to understand the role of immune-associated genes in the molecular mechanism of DR more deeply.