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Surface, M.

Publications and source records attributed to Surface, M..

2 recordsLinked to original sources

The activities of LRRK2 and GCase are positively correlated in clinical biospecimens and experimental models of Parkinson's disease

LRRK2 is a kinase involved in different cellular functions, including autophagy, endolysosomal pathways and vesicle trafficking. Mutations in LRRK2 cause autosomal dominant forms of Parkinsons disease (PD). Heterozygous mutations in GBA1, the gene encoding the lysosomal enzyme glucocerebrosidase (GCase), are the most common genetic risk factors for PD. Moreover, GCase function is altered in idiopathic PD and in other genetic forms of the disease. Recent work suggests that LRRK2 kinase activity can regulate GCase function. However, both a positive and a negative correlation have been described. To gain insights into the impact of LRRK2 on GCase, we investigated GCase levels and activity in LRRK2 G2019S knockin mice, in clinical biospecimens from PD patients carrying this mutation and in patient-derived cellular models. In these models we found a positive correlation between the activities of LRRK2 and GCase, which was further confirmed in cell lines with genetic and pharmacological manipulation of LRRK2 kinase activity. Overall, our study indicates that LRRK2 kinase activity affects both the levels and the catalytic activity of GCase.

neuroscience↗

Urinary proteome profiling for stratifying patients with familial Parkinsons disease

The prevalence of Parkinsons disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive and non-invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non-carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone was sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP and other PD-associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD.

systems biology↗