Differential serum microRNAs in premotor LRRK2 G2019S carriers from Parkinson's disease

Circulating microRNAs May Be Predictive of Degenerative Cervical Myelopathy

STUDY DESIGN

Basic Science.

OBJECTIVE

The objective of this study was to identify a unique serum profile of circulating miRNAs and inflammatory markers in patients with degenerative cervical myelopathy (DCM) compared with healthy controls (HC).

SUMMARY OF BACKGROUND DATA

Currently, DCM is diagnosed with a combination of history, physical examination, and close correlation to advanced imaging. To date, no serum marker has been identified to be diagnostic of this condition.

METHODS

Whole venous blood was collected from patients with DCM as well as healthy age-matched and gender-matched controls. miRNA was extracted from venous blood, and a screening analysis was initially conducted to identify miRNA dysregulation in DCM patients. RT-qPCR was used to analyze the expression of 2 specific miRNAs based on screening analysis and literature review. Bioinformatics analysis was used to identify gene networks and potential targets of the miRNA. In addition, the serum inflammatory profile of DCM and HC groups was differentiated using a pro-inflammatory panel.

RESULTS

Thirty-six patients were enrolled in the DCM group (36.1% male, 61.5±9.5 y), while 35 patients were enrolled in the HC group (31.4% male, 57.5±8.9 y). Of the 15 total miRNAs differentially expressed between DCM and HC groups, two were selected for further analysis: miR-223-3p (upregulated) and miR-451a (downregulated). Functional gene network analysis revealed the highest-ranking gene network was involved in neurological disease, while the most overexpressed miRNA in this network (miR-233-3p) was noted to have over 100 targets, including CDKN1B and the insulin receptor. Serum cytokine analysis showed significant upregulation of several pro-inflammatory cytokines in the DCM cohort compared with the HC group.

CONCLUSION

DCM patients demonstrated a set of unique circulating miRNAs in addition to a different serum inflammatory profile compared with HC. These miRNAs may potentially serve as targets for future therapeutic intervention or diagnostic/prognostic testing.

The identification of biomarkers for Alzheimer's disease using a systems biology approach based on lncRNA-circRNA-miRNA-mRNA ceRNA networks

In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer's disease.

Converging peripheral blood microRNA profiles in Parkinson's disease and progressive supranuclear palsy

MicroRNAs act via targeted suppression of messenger RNA translation in the DNA-RNA-protein axis. The dysregulation of microRNA(s) reflects the epigenetic changes affecting the cellular processes in multiple disorders. To understand the complex effect of dysregulated microRNAs linked to neurodegeneration, we performed a cross-sectional microRNA expression analysis in idiopathic Parkinson's disease (n = 367), progressive supranuclear palsy (n = 35) and healthy controls (n = 416) from the Luxembourg Parkinson's Study, followed by prediction modelling, enriched pathway analysis and target simulation of dysregulated microRNAs using probabilistic Boolean modelling. Forty-six microRNAs were identified to be dysregulated in Parkinson's disease versus controls and 16 in progressive supranuclear palsy versus controls with 4 overlapping significantly dysregulated microRNAs between the comparisons. Predictive power of microRNA subsets (including up to 100 microRNAs) was modest for differentiating Parkinson's disease or progressive supranuclear palsy from controls (maximal cross-validated area under the receiver operating characteristic curve 0.76 and 0.86, respectively) and low for progressive supranuclear palsy versus Parkinson's disease (maximal cross-validated area under the receiver operating characteristic curve 0.63). The enriched pathway analysis revealed natural killer cell pathway to be dysregulated in both, Parkinson's disease and progressive supranuclear palsy versus controls, indicating that the immune system might play an important role in both diseases. Probabilistic Boolean modelling of pathway dynamics affected by dysregulated microRNAs in Parkinson's disease and progressive supranuclear palsy revealed partially overlapping dysregulation in activity of the transcription factor EB, endoplasmic reticulum stress signalling, calcium signalling pathway, dopaminergic transcription and peroxisome proliferator-activated receptor gamma coactivator-1α activity, though involving different mechanisms. These findings indicated a partially convergent (sub)cellular end-point dysfunction at multiple levels in Parkinson's disease and progressive supranuclear palsy, but with distinctive underlying molecular mechanisms.

Systematic genome-wide Mendelian randomization reveals the causal links between miRNAs and Parkinson's disease

Background

MicroRNAs (miRNAs) have pivotal roles in gene regulation. Circulating miRNAs have been developed as novel candidate non-invasive biomarkers for diagnosis, prognosis, and treatment response for diseases. However, miRNAs that have causal effects on Parkinson's Disease (PD) remain largely unknown. To investigate the causal relationships between miRNAs and PD, here we conduct a Mendelian randomization (MR) study.

Methods

This study utilized the summary-level data of respective genome-wide association studies (GWAS) for 2083 miRNAs and seven PD-related outcomes to comprehensively reveal the causal associations between the circulating miRNAs and PD. Two-sample MR design was deployed and the causal effects were estimated with inverse variance weighted, MR-Egger, and weighted median. Comprehensively sensitive analyses were followed, including Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis, to validate the robustness of our results. Finally, we investigated the potential role of the MR significant miRNAs by predicting their target genes and functional enrichment analysis.

Results

Inverse variance weighted estimates suggested that two miRNAs, miR-205-5p (β = -0.46, 95%CI: -0.690 to -0.229, p = 9.3 × 10-5) and miR-6800-5p (β = -0.389, 95%CI: -0.575 to -0.202, p = 4.32 × 10-5), significantly decreased the rate of cognitive decline among PD patients. In addition, eight miRNAs were nominally associated with more than three PD-related outcomes each. No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. Gene Ontology (GO) analysis showed that the targets of these causal miRNAs were significantly enriched in cell cycle, apoptotic, and aging pathways.

Conclusion

This MR study identified two miRNAs whose genetically regulated expression might have a causal role in the development of PD dementia. Our findings provided potential miRNA biomarkers to make better and early diagnoses and risk assessments of PD.

miR-221 and Parkinson's disease: A biomarker with therapeutic potential

Parkinson's disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra, leading to various motor and non-motor symptoms. Several cellular and molecular mechanisms such as alpha-synuclein (α-syn) accumulation, mitochondrial dysfunction, oxidative stress and neuroinflammation are involved in the pathogenesis of this disease. MicroRNAs (miRNAs) play important roles in post-transcriptional gene regulation. They are typically about 21-25 nucleotides in length and are involved in the regulation of gene expression by binding to the messenger RNA (mRNA) molecules. miRNAs like miR-221 play important roles in various biological processes, including development, cell proliferation, differentiation and apoptosis. miR-221 promotes neuronal survival against oxidative stress and neurite outgrowth and neuronal differentiation. Additionally, the role of miR-221 in PD has been investigated in several studies. According to the results of these studies, (1) miR-221 protects PC12 cells against oxidative stress induced by 6-hydroxydopamine; (2) miR-221 prevents Bax/caspase-3 signalling activation by stopping Bim; (3) miR-221 has moderate predictive power for PD; (4) miR-221 directly targets PTEN, and PTEN over-expression eliminates the protective action of miR-221 on p-AKT expression in PC12 cells; and (5) miRNA-221 controls cell viability and apoptosis by manipulating the Akt signalling pathway in PD. This review study suggested that miR-221 has the potential to be used as a clinical biomarker for PD diagnosis and stage assignment.

Using Extracellular miRNA Signatures to Identify Patients with LRRK2-Related Parkinson's Disease

Background

Mutations in the Leucine Rich Repeat Kinase 2 gene are highly relevant in both sporadic and familial cases of Parkinson's disease. Specific therapies are entering clinical trials but patient stratification remains challenging. Dysregulated microRNA expression levels have been proposed as biomarker candidates in sporadic Parkinson's disease.

Objective

In this proof-of concept study we evaluate the potential of extracellular miRNA signatures to identify LRRK2-driven molecular patterns in Parkinson's disease.

Methods

We measured expression levels of 91 miRNAs via RT-qPCR in ten individuals with sporadic Parkinson's disease, ten LRRK2 mutation carriers and eleven healthy controls using both plasma and cerebrospinal fluid. We compared miRNA signatures using heatmaps and t-tests. Next, we applied group sorting algorithms and tested sensitivity and specificity of their group predictions.

Results

miR-29c-3p was differentially expressed between LRRK2 mutation carriers and sporadic cases, with miR-425-5p trending towards significance. Individuals clustered in principal component analysis along mutation status. Group affiliation was predicted with high accuracy in the prediction models (sensitivity up to 89%, specificity up to 70%). miRs-128-3p, 29c-3p, 223-3p, and 424-5p were identified as promising discriminators among all analyses.

Conclusions

LRRK2 mutation status impacts the extracellular miRNA signature measured in plasma and separates mutation carriers from sporadic Parkinson's disease patients. Monitoring LRRK2 miRNA signatures could be an interesting approach to test drug efficacy of LRRK2-targeting therapies. In light of small sample size, the suggested approach needs to be validated in larger cohorts.