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Combinatory microRNA serum signatures as classifiers of Parkinson's disease.
Parkinsonism Relat Disord. 2019 07; 64:202-210.PR

Abstract

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.

Authors+Show Affiliations

Department of Biological Sciences, St. John's University, New York, NY, USA .Department of Biological Sciences, St. John's University, New York, NY, USA .Norwegian Center for Movement Disorders, Stavanger University Hospital, Stavanger, Norway.Kimmel Center for Biology and Medicine at the Skirball Institute and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.Norwegian Center for Movement Disorders, Stavanger University Hospital, Stavanger, Norway.Norwegian Center for Movement Disorders, Stavanger University Hospital, Stavanger, Norway; Department of Chemistry, Bioscience and Environmental Engineering, University of Stavanger, Norway.Department of Computer Science, Mathematics and Science, St. John's University, New York, NY, USA.Department of Clinical Medicine, University of Bergen, Bergen, Norway; Department of Neurology, Haukeland University Hospital, Bergen, Norway.Department of Pharmacology and Clinical Neuroscience, University of Umeå, Umeå, Sweden.Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College, London, UK; Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway.Kimmel Center for Biology and Medicine at the Skirball Institute and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.Network for Medical Sciences, University of Stavanger, Stavanger, Norway.Norwegian Center for Movement Disorders, Stavanger University Hospital, Stavanger, Norway; Department of Chemistry, Bioscience and Environmental Engineering, University of Stavanger, Norway.Department of Biological Sciences, St. John's University, New York, NY, USA . Electronic address: mollers@stjohns.edu.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

31003905

Citation

Patil, Ketan S., et al. "Combinatory microRNA Serum Signatures as Classifiers of Parkinson's Disease." Parkinsonism & Related Disorders, vol. 64, 2019, pp. 202-210.
Patil KS, Basak I, Dalen I, et al. Combinatory microRNA serum signatures as classifiers of Parkinson's disease. Parkinsonism Relat Disord. 2019;64:202-210.
Patil, K. S., Basak, I., Dalen, I., Hoedt, E., Lange, J., Lunde, K. A., Liu, Y., Tysnes, O. B., Forsgren, L., Aarsland, D., Neubert, T. A., Larsen, J. P., Alves, G., & Møller, S. G. (2019). Combinatory microRNA serum signatures as classifiers of Parkinson's disease. Parkinsonism & Related Disorders, 64, 202-210. https://doi.org/10.1016/j.parkreldis.2019.04.010
Patil KS, et al. Combinatory microRNA Serum Signatures as Classifiers of Parkinson's Disease. Parkinsonism Relat Disord. 2019;64:202-210. PubMed PMID: 31003905.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Combinatory microRNA serum signatures as classifiers of Parkinson's disease. AU - Patil,Ketan S, AU - Basak,Indranil, AU - Dalen,Ingvild, AU - Hoedt,Esthelle, AU - Lange,Johannes, AU - Lunde,Kristin A, AU - Liu,Ying, AU - Tysnes,Ole-Bjørn, AU - Forsgren,Lars, AU - Aarsland,Dag, AU - Neubert,Thomas A, AU - Larsen,Jan Petter, AU - Alves,Guido, AU - Møller,Simon Geir, Y1 - 2019/04/11/ PY - 2019/01/05/received PY - 2019/03/22/revised PY - 2019/04/10/accepted PY - 2019/4/21/pubmed PY - 2020/5/22/medline PY - 2019/4/21/entrez KW - Alzheimer's disease KW - Biomarker KW - Parkinson's disease KW - microRNA SP - 202 EP - 210 JF - Parkinsonism & related disorders JO - Parkinsonism Relat Disord VL - 64 N2 - 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. SN - 1873-5126 UR - https://www.unboundmedicine.com/medline/citation/31003905/Combinatory_microRNA_serum_signatures_as_classifiers_of_Parkinson's_disease_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1353-8020(19)30205-6 DB - PRIME DP - Unbound Medicine ER -