Proteomics and machine learning identify a distinct biomarker panel to detect prodromal and early Parkinson’s disease-Reference-Cited by-同舟云学术

Proteomics and machine learning identify a distinct biomarker panel to detect prodromal and early Parkinson’s disease

Published:2023-04-17 Issue: Volume: Page:
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Author:

Hällqvist Jenny¹,Bartl Michael²^ORCID,Dakna Mohammed²,Schade Sebastian³^ORCID,Garagnani Paolo⁴^ORCID,Bacalini Maria-Giulia⁵,Pirazzini Chiara⁴,Bhatia Kailash⁶^ORCID,Schreglmann Sebastian R.⁷^ORCID,Xylaki Mary²,Weber Sandrina²,Ernst Marielle⁸,Muntean Maria-Lucia³,Sixel-Döring Friederike⁹,Franceschi Claudio⁴^ORCID,Doykov Ivan¹⁰,Trenkwalder Claudia¹¹,Heywood Wendy E.¹⁰^ORCID,Consortium PROPAGE-AGEING,Mills Kevin¹²,Mollenhauer Brit¹³^ORCID

Affiliation:

1. UCL Institute of Child Health and Great Ormond Street Hospital, London, UK; UCL Queen Square Institute of Neurology, Clinical and Movement Neurosciences, London, UK

2. Department of Neurology, University Medical Center Goettingen, Germany

3. Paracelsus-Elena-Klinik, Kassel, Germany

4. Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy

5. IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy

6. UCL Queen Square Institute of Neurology, Clinical and Movement Neurosciences, London, UK; National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N3BG

7. UCL Queen Square Institute of Neurology, Clinical and Movement Neurosciences, London, UK; National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N3BG; Department of Neurology, University Hospital Wuerzburg, Josef-Schneiderstr. 11, 97080 Wuerzburg, Germany

8. Institute of Diagnostic and Interventional Neuroradiology, University Medical Center Goettingen, Germany

9. Paracelsus-Elena-Klinik, Kassel, Germany; Department of Neurology, Philipps-University, Marburg, Germany

10. UCL Institute of Child Health and Great Ormond Street Hospital, London, UK

11. Paracelsus-Elena-Klinik, Kassel, Germany; Department of Neurosurgery, University Medical Center Goettingen, Robert-Koch Str. 40, 37075 Goettingen, Germany

12. UCL Queen Square Institute of Neurology, Clinical and Movement Neurosciences, London, UK

13. Department of Neurology, University Medical Center Goettingen, Germany; Paracelsus-Elena-Klinik, Kassel, Germany

Abstract

Abstract Parkinson’s disease (PD) is an increasingly prevalent neurodegenerative disease for which readily available and non-invasive diagnostic biomarkers are scarce. Here, we present a panel of proteomic plasma biomarkers, capable of discriminating between PD and healthy controls with 100% accuracy in a machine learning model. We performed a discovery proteomics study on newly diagnosed PD patients and controls, followed by a multiplexed targeted proteomic assay applied to 99 de novo PD patients and 36 controls. The machine learning model correctly classified all patients, and multiple markers correlated with motor, non-motor symptom severity and cognitive decline. We also evaluated 18 prodromal subjects with iRBD and predicted 72 - 94% of the iRBD samples as PD. This figure matches the clinical conversion rate observed in PD, identifying a pattern already evident in iRBD and indicating pre-symptomatic molecular events. These findings may advance our understanding and supporting of future clinical trials.

Publisher

Research Square Platform LLC

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