Expression Profiling of Blood microRNAs 885, 361, and 17 in the Patients with the Parkinson’s disease: Integrating Interaction Data to Uncover the Possible Triggering Age-Related Mechanisms

Abstract

MicroRNAs (miRNAs) have been reported to contribute to the pathophysiology of the Parkinson’s disease (PD), an age related-neurodegenerative disorder. The aim of present study was to compare the expression profiles of a new set of candidate miRNAs related to aging and cellular senescence in peripheral blood mononuclear cells (PBMCs) obtained from the PD patients with healthy controls and then in the early and advanced stages of the PD patients with their controls to clarify whether their expression was correlated with the disease severity. We have also proposed a consensus-based strategy to interpret the miRNAs expression data to gain a better insight into the molecular regulatory alterations during the incidence of PD. We evaluated the miRNA expression levels in the PBMCs obtained from 36 patients with PD and 16 healthy controls by the reverse transcription-quantitative real-time PCR and their performance to discriminate the PD patients from the healthy subjects assessed using the receiver operating characteristic curve analysis. Also, we applied our consensus and integration approach to construct a deregulated miRNA-based network in PD with the respective targets and transcription factors, and the enriched gene ontology and pathways using the enrichment analysis approach were obtained. There was a significant overexpression of miR-885 and miR-17 and the downregulation of miR-361 in the PD patients compared to the controls. The blood expression of miR-885 and miR-17 tended to increase along with the disease severity. On the other hand, the lower levels of miR-361 in the early stages of the PD patients, as compared to controls, and its higher levels in the advanced stages of PD patients, as compared to the early stages of the PD patients, were observed. Combination of all three miRNAs showed an appropriate value of AUC (0.985) to discriminate the PD patients from the healthy subjects. Also, the deregulated miRNAs were linked to the known PD pathways and the candidate related target genes were presented. We revealed 3 candidate biomarkers related to aging and cellular senescence for the first time in the patients with PD. Our in-silico analysis identified candidate target genes and TFs, including those related to neurodegeneration and PD. Overall, our findings provided novel insights into the probable age-regulatory mechanisms underlying PD and a rationale to further clarify the role of the identified miRNAs in the PD pathogenesis.

Serum MicroRNAs Predict Isolated Rapid Eye Movement Sleep Behavior Disorder and Lewy Body Diseases

“… 32 , 43 , 47 , 48 , 49 In summary, most of the 12 biosignature miRNAs were earlier reported in α‐synucleinopathy. 5 , 6 , 7 , 10 , 21 , 22 , 33 , 36 , 37 , 38 , 39 , 40 , 41 , 42 This is relevant given that, if validated, our findings may have implications for other PD at‐risk cohorts, such as individuals with hyposmia or LRRK2 or GBA asymptomatic mutation carriers.…”

“…By machine learning, we evaluated the disease prediction capacity of the combined expression levels from the 12 miRNA biosignatures adjusted by age and sex to estimate each proband's probability of disease, IRBD and PD/DLB versus being control and without any further clinical or imaging input. The miRNA biosignature achieved a high discriminative capacity with an AUC of 98% (95% CI: 89–99%) and distinguished prodromal and manifest PD or DLB from controls more accurately than other previously proposed candidate biomarkers, including α‐synuclein 8,32‐35 . The predictive model also accurately classified both positive and negative individuals (94% accuracy), specifically identifying true positives (98% sensitivity).…”

“…The miRNA biosignature achieved a high discriminative capacity with an AUC of 98% (95% CI: 89-99%) and distinguished prodromal and manifest PD or DLB from controls more accurately than other previously proposed candidate biomarkers, including α-synuclein. 8,[32][33][34][35] The predictive model also accurately classified both positive and negative individuals (94% accuracy), specifically identifying true positives (98% sensitivity). However, while the fraction of false negatives was only 2%, the false-positive rate was 14% (86% specificity).…”

Modified level of miR‐376a is associated with Parkinson's disease

“…Although a wide variety of studies use patients' sera to examine non-coding RNAs profiles, their sources should be further clarified. However, similarities in transcript patterns of a number of such factors, in both PBMC and brain in PD, provide us a reason to assess such factors in PBMC 22. Accordingly, we investigated gene expression's differences in both acute and chronic in vitro PD models as well as PBMCs of patients with PD.Although the root cause of sporadic PD is intricate and elusive, multiple lines of evidence associate its pathogenesis to mitochondrial dysfunction.…”

Evolutionary Changes in the Interaction of miRNA With mRNA of Candidate Genes for Parkinson’s Disease

“…Unfortunately, at present, there are no effective methods for the early diagnosis of this disease, which significantly reduces the effects of treatment ( Arshad et al, 2017 ; Patil et al, 2019 ). The difficulty of diagnosing PD is attributable to the many genes that participate in the development of this disease (candidate genes), the expression of which changes with the development of several types of neurodegenerative diseases ( Behbahanipour et al, 2019 ). To date, several dozen candidate PD genes have been identified, and their roles in PD must be investigated.…”