Study Rationale:
There is an urgent need for disease indicators — also known as biomarkers — in Parkinson’s disease to enable early diagnoses and treatment response monitoring. Urine is a promising body fluid for biomarker discovery, as it can be easily and non-invasively collected and contains proteins from distal organs (far from the center of the body) including the brain. Recent technological advances in mass spectrometry (MS)-based proteomics (the large-scale study of proteins) now allow the precise quantification of hundreds to thousands of proteins in urine. The application of state-of-the-art mass spectrometry-based proteomics to urine samples is thus a promising approach to identify sensitive and non-invasive biomarkers for Parkinson’s disease and improves our understanding of the role of the LRRK2 gene in Parkinson’s. Mutations in the LRRK2 gene are the most common cause of familial Parkinson’s.
Hypothesis:
This study aims to validate the chemical process called phosphorylation in Rab proteins as a surrogate marker for LRRK2 activity and by using correlation analyses improve our understanding of the role of LRRK in urine levels. Furthermore, it seeks to identify new biomarkers for Parkinson’s and LRRK2/GBA genes.
Study Design:
In this study, the investigators will determine hundreds of proteomes of urine samples from Parkinson’s patients and control volunteers with or without a mutation in LRRK2 and GBA. Applying two forms of an advanced mass spectrometry-based proteomics workflow, they will quantify the abundances of about 2,000 proteins in each urine sample and determine the phosphorylation state of Rab10 and LRRK2. Furthermore, statistical analyses and machine learning will help to identify potential biomarker candidates that could distinguish Parkinson’s patients from control volunteers or predict which carriers of a genetic mutation are at high risk of developing Parkinson’s.
Impact on Diagnosis/Treatment of Parkinson’s Disease:
There are multiple areas where Parkinson’s disease biomarkers in urine would make a difference for Parkinson’s patients and carriers of a genetic mutation. The availability of diagnostic biomarkers could help to diagnose patients early before brain damage occurs. Prognostic biomarkers could help identify who is at high risk of developing Parkinson’s and predictive biomarkers could be used to optimize the treatment strategy for each patient by allowing a personalized medical approach.
Next Steps for Development:
Newly identified biomarkers need to be validated in additional groups of patients to confirm their potential. In the next step, specific tests to detect these protein biomarkers reliably and with a high throughput (running large numbers of tests in a short time) in a clinical setting need to be established to enter clinical practice.