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Plasma and White Blood Cells Show Different miRNA Expression Profiles in Parkinson’s Disease

Abstract

Parkinson’s disease (PD) diagnosis is based on the assessment of motor symptoms, which manifest when more than 50% of dopaminergic neurons are degenerated. To date, no validated biomarkers are available for the diagnosis of PD. The aims of the present study are to evaluate whether plasma and white blood cells (WBCs) are interchangeable biomarker sources and to identify circulating plasma-based microRNA (miRNA) biomarkers for an early detection of PD. We profiled plasma miRNA levels in 99 l-dopa-treated PD patients from two independent data collections, in ten drug-naïve PD patients, and in unaffected controls matched by sex and age. We evaluated expression levels by reverse transcription and quantitative real-time PCR (RT-qPCR) and combined the results from treated PD patients using a fixed effect inverse-variance weighted meta-analysis. We revealed different expression profiles comparing plasma and WBCs and drug-naïve and l-dopa-treated PD patients. We observed an upregulation trend for miR-30a-5p in l-dopa-treated PD patients and investigated candidate target genes by integrated in silico analyses. We could not analyse miR-29b-3p, normally expressed in WBCs, due to the very low expression in plasma. We observed different expression profiles in WBCs and plasma, suggesting that they are both suitable but not interchangeable peripheral sources for biomarkers. We revealed miR-30a-5p as a potential biomarker for PD in plasma. In silico analyses suggest that miR-30a-5p might have a regulatory role in mitochondrial dynamics and autophagy. Further investigations are needed to confirm miR-30a-5p deregulation and targets and to investigate the influence of l-dopa treatment on miRNA expression levels.

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Acknowledgements

The authors are grateful to the study participants for their participation and collaboration in this research project. We thank Clemens Egger and Daniele di Domizio for technical support. We thank Alessandro de Grandi and Ilaria Bozzolan for their support in biobank-related issues. The authors acknowledge the help of Agatha Eisendle, Edith Kompatscher, and Monika Mair in recruiting the study participants. The authors are grateful to Deborah Mascalzoni, Fabiola Del Greco M., and Francisco Domingues for their support in ethical, statistical, and bioinformatics issues. This work was supported by the Department for Innovation and Research and University of the Autonomous Province of Bolzano.

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Authors

Contributions

C. Schwienbacher designed and supervised the study, contributed to the design of the sample collection, and wrote the manuscript. L. Foco designed and performed the statistical analyses and wrote the manuscript. A. Picard contributed to the design of the study, performed the experimental work, and wrote the manuscript. E. Corradi performed the experimental work and wrote the manuscript. A. Serafin contributed to the design of the study and performed the experimental work. J. Panzer performed the experimental work. S. Zanigni designed and contributed to the sample collection and clinical characterization of the patients. H. Blankenburg designed and performed the bioinformatics analyses and wrote the manuscript. M. Facheris designed and contributed to the sample collection and clinical characterization of the patients. G Giannini contributed to the sample collection and clinical characterization of the patients. M. Falla contributed to the clinical characterization of the patients. P. Cortelli critically revised the paper. P. Pramstaller designed and contributed to the sample collection and clinical characterization of the patients and critically revised the manuscript. A. Hicks critically revised the manuscript and contributed to the design of the sample collection and the study.

Corresponding authors

Correspondence to Christine Schwienbacher or Luisa Foco.

Ethics declarations

The local ethics committee (Comitato etico del comprensorio sanitario di Bolzano; reference numbers: 2008-D2-001090, 62/2012, 58/2013, 59/2013) approved the study, and all participants provided written informed consent.

Conflicts of Interest

C. Schwienbacher, L. Foco, A. Picard, E. Corradi, A. Serafin, J. Panzer, S. Zanigni, H. Blankenburg, M. Facheris, G. Giannini, M. Falla, and A. Hicks declare that they have no competing interests. Prof. Cortelli received honoraria for speaking engagements or consulting activities from Allergan Italia, Lilly Pharma, UCB Pharma S.p.A, Chiesi Farmaceutici, AbbVie srl, and Zambon Italy. Prof. Pramstaller received honoraria for serving on scientific boards and speaking from Novartis, Boehringer, GlaxoSmithKline, Lundbeck, and UCB.

Electronic Supplementary Material

Online Resource 1.

Clinical details of L-dopa-treated PD patients vs controls and of drug-naïve PD patients vs controls. (PDF 121 kb)

Online Resource 2.

TaqMan®miRNA assays and summary of quantitative real-time PCR experimental details. (PDF 96 kb)

Online Resource 3.

Pairplots of the differences between miRNA expression in cases-controls (SET 1, SET 2 and SET 3). The plots display the difference of expression within the matched pair for each of the studied miRNAs and for each data set. (PDF 34 kb)

Online Resource 4.

Results of the meta-analysis (SET 1 and SET 2). (PDF 7 kb)

Online Resource 5.

Forest plot of the meta-analysis for all the analysed miRNAs. The diamond indicates the pooled meta-analysis estimate of the effect (ES) and the 95% confidence interval (95% CI). I2 is provided in brackets. (PDF 4 kb)

Online Resource 6.

MiR-30a-5p target prioritization: whole data set. (XLS 1869 kb)

Online Resource 7.

Correlation between miRNA expression and PD progression in drug-naïve PD patients. (PDF 97 kb)

Online Resource 8.

Analysis on 31 matched pairs from SET 1 with miRNA expression data available in both blood and plasma. (PDF 103 kb)

Online Resource 9.

Simplified scheme of EGFR/PI3K/Akt pathway: a possible biological context for the predicted targets of miR-30a-5p. EGFR, AKT1 and DJ-1 are predicted and prioritized miR-30a-5p targets. Down-regulation of these three genes causes impairment in EGFR/PI3K/Akt pathway, which has important functions in cell survival, particularly in case of oxidative stress. White arrows: activation; red lines: inhibition. (PDF 494 kb)

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Schwienbacher, C., Foco, L., Picard, A. et al. Plasma and White Blood Cells Show Different miRNA Expression Profiles in Parkinson’s Disease. J Mol Neurosci 62, 244–254 (2017). https://doi.org/10.1007/s12031-017-0926-9

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Keywords

  • Parkinson’s disease (PD)
  • MicroRNA (miRNA)
  • Biofluid
  • Biomarker