scholarly journals Serum Exosomal miRNAs as Biomarkers of Early Diagnosis and Progression in Parkinson's Disease

2021 ◽  
Author(s):  
Qian Yang ◽  
Shulei He ◽  
Lu Huang ◽  
Ci Shao ◽  
Tiejian Nie ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Qrt Pcr ◽  
Exosomal Mirnas ◽  
Serum Exosomes

Abstract BackgroundBlood-based test for disease progression and early diagnosis of Parkinson’s disease (PD) is a long awaited but unsolved key problem in the clinic. The profiles of microRNAs (miRNAs) are regarded as potential diagnostic biomarkers in human diseases whereas the miRNAs in the periphery are susceptible to the influence of various components. MiRNAs enriched in serum exosomes have revealed disease-specific advantages for the diagnosis due to their high abundance, stability and resistant to degradation. This study aimed to screen differentially expressed exosomal miRNAs between healthy controls and PD patients to aid in diagnosis. MethodsA total of 103 healthy controls and diagnosed PD patients at different Hoehn and Yahr (H&Y) stages in Tangdu Hospital were included. In total, 185 differentially expressed miRNAs were obtained through miRNA sequencing of serum exosomes as well as edgeR and t-test analyses. Subsequently, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the commonly expressed miRNAs in all stages of PD by constructing connections between modules and specifically expressed miRNAs in each stage of PD by functional enrichment analysis. The obtained miRNAs were further validated by quantitative real-time polymerase chain reaction (qRT-PCR) with peripheral blood exosomes from 30 more participants. ResultsUsing WGCNA, it was found that 4 miRNAs were commonly associated with all the stages of PD and 13 miRNAs were specifically associated with different stages of PD. Among the 17 miRNAs, 2 were commonly expressed in all the stages of PD and 5 were specifically expressed in different stages of PD via qRT-PCR; 5 were also specifically expressed in different stages of PD by WGCNA, but validation by qRT-PCR showed inconsistent results; the remaining 5 miRNAs did not exhibit significant differences by qRT-PCR. ConclusionsThis study revealed that the 7 serum exosomal miRNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-199a-3p, hsa-miR-195-5p, hsa-miR-28-5p, hsa-miR-22-5p and hsa-miR-151a-5p) we screened out may potentially be used as biomarkers for progression and early grading diagnosis of PD in the population.

scholarly journals Several miRNAs derived from serum extracellular vesicles are potential biomarkers for early diagnosis and progression of Parkinson’s disease

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Shulei He ◽  
Lu Huang ◽  
Ci Shao ◽  
Tiejian Nie ◽  
Li Xia ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Extracellular Vesicles ◽  
Unmet Need ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Roc Curve Analysis ◽  
Qrt Pcr

Abstract Background Blood-based test for predicting disease progression and early diagnosis of Parkinson’s disease (PD) is an unmet need in the clinic. The profiles of microRNAs (miRNAs) are regarded as potential diagnostic biomarkers for human diseases, whereas miRNAs in the periphery are susceptible to the influence of various components. MiRNAs enriched in serum extracellular vesicles (EVs) have demonstrated disease-specific advantages in diagnosis due to their high abundance, stability and resistance to degradation. This study was aimed to screen differentially expressed EV-derived miRNAs between healthy controls and PD patients to aid in diagnosis of PD. Methods A total of 31 healthy controls and 72 patients with a diagnosis of PD at different Hoehn and Yahr stages in Tangdu Hospital were included. In total, 185 differentially expressed miRNAs were obtained through RNA sequencing of serum EVs as well as edgeR and t-test analyses. Subsequently, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the commonly expressed miRNAs in all stages of PD by constructing connections between modules, and specifically expressed miRNAs in each stage of PD by functional enrichment analysis. After aligning these miRNAs with PD-related miRNAs in Human miRNA Disease Database, the screened miRNAs were further validated by receiver operating characteristic (ROC) curves and quantitative real-time polymerase chain reaction (qRT-PCR) using peripheral blood EVs from 40 more participants. Results WGCNA showed that 4 miRNAs were commonly associated with all stages of PD and 13 miRNAs were specifically associated with different stages of PD. Of the 17 obtained miRNAs, 7 were validated by ROC curve analysis and 7 were verified in 40 more participants by qRT-PCR. Six miRNAs were verified by both methods, which included 2 miRNAs that were commonly expressed in all stages of PD and 4 miRNAs that were specifically expressed in different stages of PD. Conclusions The 6 serum EV-derived miRNAs, hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-199a-3p, hsa-miR-28-5p, hsa-miR-22-5p and hsa-miR-151a-5p, may potentially be used as biomarkers for PD progression and for early diagnosis of PD in populations.

scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

scholarly journals Non-invasive diagnostic tool for Parkinson’s disease by sebum RNA profile with machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuya Uehara ◽  
Shin-Ichi Ueno ◽  
Haruka Amano-Takeshige ◽  
Shuji Suzuki ◽  
Yoko Imamichi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Alpha Synuclein ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Non Invasive

AbstractParkinson'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.

scholarly journals Identification of Potential miRNA-mRNA Regulatory Network Contributing to Parkinson’s Disease

2021 ◽  
Author(s):  
Xi Yin ◽  
Miao Wang ◽  
Wei Wang ◽  
Tong Chen ◽  
Ge Song ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Rab Protein ◽  
Healthy Donors ◽  
Geo Database

Abstract Parkinson’s disease (PD) is a common neurodegenerative disease and the mechanism underlying PD pathogenesis is incompletely understood. Increasing evidence indicates that microRNA (miRNA) plays critical regulatory role in the pathogenesis of PD. This study aimed to determine the miRNA-mRNA regulatory network for PD. The differentially expressed miRNAs (DEmis) and genes (DEGs) between PD patients and healthy donors were screened from miRNA dataset GSE16658 and mRNA dataset GSE100054 downloaded from the Gene Expression Omnibus (GEO) database. Target genes of the DEmis were selected when predicted by 3 or 4 online databases and overlapped with DEGs from GSE100054. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted by Database for Annotation, Visualization and Integrated Discovery (DAVID) and Metascape analytic tool. The correlation between the screened genes and PD was evaluated by the online tool Comparative Toxicogenomics Database (CTD). The protein-protein interactions (PPI) network was built by STRING platform. Finally, we testify the expression of members of the miRNA-mRNA regulatory network in the blood samples collected from PD patients and healthy donors by using qRT-PCR. 1505 upregulated and 1302 downregulated DEGs, 77 upregulated DEmis and 112 downregulated DEmis were preliminarily screened from GEO database. Through further functional enrichment analysis, 10 PD-related hub genes were selected, including RAC1, IRS2, LEPR, PPARGC1A, CAMKK2, RAB10, RAB13, RAB27B, RAB11A and JAK2, which were mainly involved in Rab protein signaling transduction, AMPK signaling pathway and signaling by Leptin. The miRNA-mRNA regulatory network was constructed with 10 hub genes and their interacting miRNAs overlapped with DEmis, including miR-30e-5p, miR-142-3p, miR-101-3p, miR-32-3p, miR-508-5p, miR-642a-5p, miR-19a-3p and miR-21-5p. Analysis on clinical samples verified significant upregulation of LEPR and downregulation of miR-101-3p in PD patients compared with healthy donors. In the study, the potential miRNA-mRNA regulatory network was constructed in PD, which may provide novel insight into pathogenesis and treatment of PD.

scholarly journals Microarray Analysis of Transcriptome of Medulla Identifies Potential Biomarkers for Parkinson’s Disease

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiao-Yang Liao ◽  
Wei-Wen Wang ◽  
Zheng-Hui Yang ◽  
Jun Wang ◽  
Hang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Motor Nucleus ◽  
Inferior Olivary Nucleus ◽  
Potential Biomarkers

To complement the molecular pathways contributing to Parkinson’s disease (PD) and identify potential biomarkers, gene expression profiles of two regions of the medulla were compared between PD patients and control. GSE19587 containing two groups of gene expression profiles [6 dorsal motor nucleus of the vagus (DMNV) samples from PD patients and 5 from controls, 6 inferior olivary nucleus (ION) samples from PD patients and 5 from controls] was downloaded from Gene Expression Omnibus. As a result, a total of 1569 and 1647 differentially expressed genes (DEGs) were, respectively, screened in DMNV and ION with limma package ofR. The functional enrichment analysis by DAVID server (the Database for Annotation, Visualization and Integrated Discovery) indicated that the above DEGs may be involved in the following processes, such as regulation of cell proliferation, positive regulation of macromolecule metabolic process, and regulation of apoptosis. Further analysis showed that there were 365 common DEGs presented in both regions (DMNV and ION), which may be further regulated by eight clusters of microRNAs retrieved with WebGestalt. The genes in the common DEGs-miRNAs regulatory network were enriched in regulation of apoptosis process via DAVID analysis. These findings could not only advance the understandings about the pathogenesis of PD, but also suggest potential biomarkers for this disease.

scholarly journals Reduced habit-driven errors in Parkinson’s Disease

2018 ◽  
Author(s):  
Colin Bannard ◽  
Mariana Leriche ◽  
Oliver Bandmann ◽  
Christopher Brown ◽  
Elisa Ferracane ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Early Stage ◽  
Healthy Controls ◽  
Error Type ◽  
Simple Motor ◽  
Classification Of Error

Parkinson’s Disease can be understand as a disorder of motor habits. A prediction of this theory is that early stage Parkinson’s patients will display fewer errors caused by interference from previously over-learned behaviours. We test this prediction in the domain of skilled typing, where actions are easy to record and errors easy to identify. We describe a method for categorising errors as simple motor errors or habit-driven errors. We test Spanish and English participants with and without Parkinson’s, and show that indeed patients make fewer habit errors than healthy controls, and, further, that classification of error type increases the accuracy of discriminating between patients and healthy controls. As well as being a validation of a theory-led prediction, these results offer promise for automated, enhanced and early diagnosis of Parkinson’s Disease.

scholarly journals Therapeutic potential of methylxanthine drug on alpha synuclein protein in Parkinson's disease

2021 ◽  
Author(s):  
Nishant Kumar Rana ◽  
Neha Srivastava ◽  
Bhupendra Kumar ◽  
Abhishek Pathak ◽  
Vijay Nath Mishra
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neurodegenerative Disorder ◽  
Therapeutic Potential ◽  
Enrichment Analysis ◽  
Alpha Synuclein ◽  
Target Protein ◽  
Functional Enrichment ◽  
Glutamate Excitotoxicity ◽  
In Silico Docking

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer. It exists in sporadic (90 to 95%) and familial (5 to 10%) form. Its pathogenesis is due to oxidative stress, glutamate excitotoxicity, protein aggregation, neuroinflammation and neurodegeneration. There is currently no cure for this disease. The protein- protein interaction and gene ontology/functional enrichment analysis have been performed to find out the prominent interactor protein and shared common biological pathways, especially PD pathway. Further in silico docking analysis was performed on target protein to investigate the prominent drug molecule for PD. Through computational molecular virtual screening of small molecules from selected twelve natural compounds, and among these compounds methylxanthine was shown to be prominent inhibitor to SNCA protein that ultimately prevent PD. The interaction of methylxanthine compound with the target protein SNCA suggested that, it interacted with prominent binding site with good docking score and might be involved in blocking the binding of neuroinducing substances like: 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) to SNCA protein. Thus methylxanthine compounds can be explored as promising drugs for the prevention of Parkinson's disease.

Validation of Differentially Expressed Brain-Enriched microRNAs in the Plasma of Parkinson’s Disease Patients

2020 ◽  
Author(s):  
Stylianos Ravanidis ◽  
Anastasia Bougea ◽  
Nikolaos Papagiannakis ◽  
Christos Koros ◽  
Athina Simitsi ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Transcription Factor ◽  
Protein Modification ◽  
Differentially Expressed ◽  
Molecular Pathways ◽  
Healthy Controls ◽  
Neuron Development ◽  
Go Annotation ◽  
Diagnostic Potential

Abstract Background There is a pressing need to identify and validate, minimally invasive, molecular biomarkers that will complement current practices and increase the diagnostic accuracy in Parkinson’s disease (PD). Brain-enriched miRNAs regulate all aspects of neuron development and function; importantly, they are secreted by neurons in amounts that can be readily detected in the plasma. Τhe aim of the present study was to validate a set of previously identified brain-enriched miRNAs with a diagnostic potential for idiopathic PD and recognize the molecular pathways affected by these deregulated miRNAs.Methods RT-qPCR was performed in the plasma of 92 healthy controls and 108 idiopathic PD subjects. Statistical and in silico analyses were used to validate deregulated miRNAs and pathways in PD, respectively.Results miR-22-3p, miR-124-3p, miR-136-3p, miR-154-5p and miR-323a-3p levels were found to be differentially expressed between healthy controls and PD patients. miR-330-5p, miR-433-3p and miR-495-3p levels were overall higher in male subjects. Most of these miRNAs are clustered at Chr14q32 displaying CREB1, CEBPB, and MAZ transcription factor binding sites. Gene Ontology (GO) annotation analysis of deregulated miRNA targets revealed that ‘Protein modification’, ‘Transcription factor activity’ and ‘Cell death’ terms were over-represented. Kyoto Encyclopedia of Genes and Genome (KEGG) analysis revealed that ‘Long-term depression’, ‘TGF-beta signaling’, and ‘FoxO signaling’ pathways were significantly affected.Conclusions We validated a panel of brain-enriched miRNAs that can be used along with other measures for the detection of PD, revealed molecular pathways targeted by these deregulated miRNAs, and identified upstream transcription factors that may be directly implicated in their regulation and thereafter PD pathogenesis.

scholarly journals Transcriptomic Profiling of Circular RNA in Different Brain Regions of Parkinson’s Disease in a Mouse Model

2020 ◽  
Vol 21 (8) ◽  
pp. 3006 ◽  
Author(s):  
Erteng Jia ◽  
Ying Zhou ◽  
Zhiyu Liu ◽  
Liujing Wang ◽  
Tinglan Ouyang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Mouse Model ◽  
Signaling Pathway ◽  
Target Genes ◽  
Kegg Pathway ◽  
Brain Regions ◽  
Differentially Expressed ◽  
Sequencing Analysis ◽  
Qrt Pcr

Parkinson’s disease (PD) is the second most common neurodegenerative disease and although many studies have been done on this disease, the underlying mechanisms are still poorly understood and further studies are warranted. Therefore, this study identified circRNA expression profiles in the cerebral cortex (CC), hippocampus (HP), striatum (ST), and cerebellum (CB) regions of the 1-methyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model using RNA sequencing (RNA-seq), and differentially expressed circRNA were validated using reverse transcription quantitative real-time PCR (qRT-PCR). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and competing endogenous RNA (ceRNA) network analyses were also performed to explore the potential function of circRNAs. The results show that, compared with the control group, 24, 66, 71, and 121 differentially expressed circRNAs (DE-circRNAs) were found in the CC, HP, ST, and CB, respectively. PDST vs. PDCB, PDST vs. PDHP, and PDCB vs. PDHP groups have 578, 110, and 749 DE-circRNAs, respectively. Then, seven DE-cirRNAs were selected for qRT-PCR verification, where the expressions were consistent with the sequencing analysis. The GO and KEGG pathway analyses revealed that these DE-circRNAs participate in several biological functions and signaling pathways, including glutamic synapse, neuron to neuron synapse, cell morphogenesis involved in neuron differentiation, Parkinson’s disease, axon guidance, cGMP-PKG signaling pathway, and PI3K-Akt signaling pathway. Furthermore, the KEGG analysis of the target genes predicted by DE-circRNAs indicated that the target genes predicted by mmu_circRNA_0003292, mmu_circRNA_0001320, mmu_circRNA_0005976, and mmu_circRNA_0005388 were involved in the PD-related pathway. Overall, this is the first study on the expression profile of circRNAs in the different brain regions of PD mouse model. These results might facilitate our understanding of the potential roles of circRNAs in the pathogenesis of PD. Moreover, the results also indicate that the mmu_circRNA_0003292-miRNA-132-Nr4a2 pathway might be involved in the regulation of the molecular mechanism of Parkinson’s disease.

scholarly journals Circulating CircRNAs Panel Acts as a Biomarker for the Early Diagnosis and Severity of Parkinson’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Lingling Zhong ◽  
KeJu Ju ◽  
Ainian Chen ◽  
Hua Cao
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Disease Progression ◽  
Clinical Symptoms ◽  
Early Stage ◽  
Healthy Controls ◽  
Training Set ◽  
The Central Nervous System

Parkinson’s disease (PD) is a chronic and progressive degenerative disease of the central nervous system. Degenerative neuropathy can occur in patients with PD even before typical clinical symptoms appear in the preclinical stage. Therefore, if the early diagnosis of degenerative diseases can be timely and the correlation with the disease progression can be explored, the disease progression will be slowed down and the quality of life of patients will be improved. In this study, the circRNA microarray was employed to screen the dysregulated circRNA in plasma samples of PD. Four circRNAs (circ_0085869, circ_0004381, circ_0017204, and circ_0090668) were obtained with increased levels in PD patients by cross comparison and preliminary verification in PD comparing with healthy controls. Further validation found the circRNA panel was consistent with the training set. The ROC curve also revealed a high diagnostic ability of circ_0004381 and circ_0017204 in predicting the early stage of PD from healthy controls. circ_0085869, circ_0004381, circ_0017204, and circ_0090668 also presented a high ability to distinguish the late stage of PD from early stage. In conclusion, circulating circRNA panel might be a potential fingerprint for predicting the early diagnosis of PD and may act as a biomarker for disease progression.

Sign in / Sign up

Export Citation Format

Share Document