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Combinatory microRNA serum signatures as classifiers of Parkinson's disease
Ketan S Patil1, Indranil Basak1, Ingvild Dalen2
1Department of Biological Sciences, St. John's University, New York, NY, USA .
Introduction:
As current clinical diagnostic protocols for Parkinson's disease (PD) may be prone to inaccuracies there is a need to identify and validate molecular biomarkers, such as circulating microRNAs, which will complement current practices and increase diagnostic accuracy. This study identifies, verifies and validates combinatory serum microRNA signatures as diagnostic classifiers of PD across different patient cohorts.
Methods:
370 PD (drug naïve) and control serum samples from the Norwegian ParkWest study were used for identification and verification of differential microRNA levels in PD which were validated in a blind study using 64 NY Parkinsonism in UMeå (NYPUM) study serum samples and tested for specificity in 48 Dementia Study of Western Norway (DemWest) study Alzheimer's disease (AD) serum samples using miRNA-microarrays, and quantitative (q) RT-PCR. Proteomic approaches identified potential molecular targets for these microRNAs.
Results:
Using Affymetrix GeneChip® miRNA 4.0 arrays and qRT-PCR we comprehensively analyzed serum microRNA levels and found that the microRNA (PARKmiR)-combinations, hsa-miR-335-5p/hsa-miR-3613-3p (95% CI, 0.87-0.94), hsa-miR-335-5p/hsa-miR-6865-3p (95% CI, 0.87-0.93), and miR-335-5p/miR-3613-3p/miR-6865-3p (95% CI, 0.87-0.94) show a high degree of discriminatory accuracy (AUC 0.9-1.0). The PARKmiR signatures were validated in an independent PD cohort (AUC ≤ 0.71) and analysis in AD serum samples showed PARKmiR signature specificity to PD. Proteomic analyses showed that the PARKmiRs regulate key PD-associated proteins, including alpha-synuclein and Leucine Rich Repeat Kinase 2.
Conclusions:
Our study has identified and validated unique miRNA serum signatures that represent PD classifiers, which may complement and increase the accuracy of current diagnostic protocols.
Insights
This study identifies novel serum microRNA signatures (PARKmiR) to improve Parkinson's disease (PD) diagnosis. These biomarkers show high accuracy and specificity, potentially enhancing current diagnostic methods for PD.
Area of Science:
- Biomarkers
- Neuroscience
- Genetics
Background:
- Current Parkinson's disease (PD) diagnostic protocols may lack accuracy.
- There is a need for reliable molecular biomarkers to improve PD diagnosis.
- Circulating microRNAs (miRNAs) are promising candidates for diagnostic biomarkers.
Purpose of the Study:
- To identify, verify, and validate serum microRNA signatures as diagnostic classifiers for PD.
- To assess the accuracy and specificity of these microRNA signatures in independent cohorts.
- To explore the regulatory role of identified microRNAs in PD-associated proteins.
Main Methods:
- Serum samples from PD patients (Norwegian ParkWest study) and controls were analyzed.
- MicroRNA levels were quantified using miRNA-microarrays and quantitative RT-PCR.
- Proteomic approaches were used to identify molecular targets of the microRNAs.
Main Results:
- Combinatory serum microRNA signatures (PARKmiR) demonstrated high discriminatory accuracy (AUC 0.9-1.0).
- The identified PARKmiR signatures were validated in an independent PD cohort (AUC ≤ 0.71).
- PARKmiR signatures showed specificity to PD when tested in Alzheimer's disease samples.
Conclusions:
- Unique serum microRNA signatures (PARKmiR) have been identified and validated as PD classifiers.
- These signatures can complement current diagnostic protocols and enhance diagnostic accuracy for Parkinson's disease.
- The identified microRNAs regulate key PD-associated proteins, including alpha-synuclein.