MicroRNAs are reportedly involved in the pathogenesis of neurodegenerative diseases, including Parkinson's disease and multiple system atrophy. We previously identified 7 differentially expressed microRNAs in Parkinson's disease patients and control sera (miR-30c, miR-31, miR-141, miR-146b-5p, miR-181c, miR-214, and miR-193a-3p). To investigate the expression levels of the 7 serum microRNAs in Parkinson's disease and multiple system atrophy, 23 early Parkinson's disease patients (who did not take any anti- Parkinson's disease drugs), 23 multiple system atrophy patients, and 24 normal controls were recruited at outpatient visits in this study. The expression levels of the 7 microRNAs in serum were detected using quantitative real-time polymerase chain reaction. A receiver operating characteristic curve was used to evaluate whether microRNAs can differentially diagnose Parkinson's disease and multiple system atrophy. Clinical scales were used to analyze the correlations between serum microRNAs and clinical features. The results indicated that miR-214 could distinguish Parkinson's disease from the controls, and another 3 microRNAs could differentiate multiple system atrophy from the controls (miR-141, miR-193a-3p, and miR-30c). The expression of miR-31, miR-141, miR-181c, miR-193a-3p, and miR-214 were lower in multiple system atrophy than in Parkinson's disease (all < 0.05). Combinations of microRNAs accurately discriminated Parkinson's disease from multiple system atrophy (area under the receiver operating characteristic curve = 0.951). For the correlation analysis, negative correlations were discovered between the expression of miR-214 and the Hamilton Anxiety Scale and Parkinson's Disease Non-Motor Symptom scores (all < 0.05). Our results demonstrate that the distinctive characteristics of microRNAs differentiate Parkinson's disease and multiple system atrophy patients from healthy controls and may be used for the early diagnosis of Parkinson's disease and multiple system atrophy.

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http://dx.doi.org/10.31083/j.jin.2020.03.163DOI Listing

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