NCER-PD - National Centre for Excellence in Research on Parkinson’s Disease - LCSB

NCER-PD is an international cross-disciplinary research initiative on Parkinson’s disease based in Luxembourg.

The project at a glance

Start date:

01 Jun 2015
Duration in months:

96
Funding:

Luxembourg National Research Fund (FNR) / Michael J Fox Foundation (MJFF)
Principal Investigator(s):

Rejko Krüger

Reinhard Schneider

Anne Grünewald

Michel Mittelbronn (external)

Britt Mollenhauer (external)

Michele Hu (external)

About

NCER-PD (funded by the Luxembourg National Research Fund (FNR)) unites Luxembourg’s clinical, biomedical, and computational research. Within the second funding period (2019-2023), the aim is to establish emerging precision medicine concepts for Parkinson’s disease (PD), including earlier diagnosis, patient stratification, and personalised treatments.

In its first four years, NCER-PD established a nation-wide and deeply phenotyped cohort of more than 1,600 participants from Luxembourg and the Greater Region. This cohort included patients diagnosed with PD and other forms of parkinsonism, and matching control subjects. Research physicians, psychologists, and study nurses routinely collect clinical and neuropsychological data, as well as biosamples such as blood, urine, stool, and saliva. These data and samples are then stored, curated, and integrated into state-of-the-art data and biobank facilities for processing within the NCER-PD programme and beyond.

During its second funding phase, NCER-PD is harvesting the collected data and exploring new avenues of biomedical research aiming to translate findings into therapies for PD. Besides sustaining the Parkinson’s cohort, two at-risk cohorts have been set up. One is of people with prodromal PD defined by REM sleep behaviour disorder (RBD) to identify preclinical biomarkers preceding the clinical evolution of PD and define future strategies for treatments in early disease stages. The second is of people with GBA gene mutations (the most common genetic risk factor for PD) to identify brain imaging biomarkers for early diagnosis. Building on computational modelling, we aim to integrate functional modelling in patient-derived cellular models. The latter will be used as personalised clinical trials in a dish to validate identified biomarkers and test novel compounds using a robotic platform.