The gateway to Europe's
integrated metrology community.

Innovative measurements for improved diagnosis and management of neurodegenerative diseases

Short Name: NeuroMet, Project Number: 15HLT04
Image showing a MRI scan of a human head
MRI scan of a human head

Improving techniques to monitor progression and treatment success for Alzheimer’s and Parkinson’s diseases

Neurodegeneration is an incurable, debilitating process inflicting a growing medical and economic toll on society and Alzheimer’s disease (AD) and Parkinson’s disease (PD) are two of the most common neurodegenerative diseases (NDDs). Whilst symptoms differ there are similarities in the underlying changes with both involving the build-up of proteins in the brain and the destruction of brain cells. Early detection and treatment can reduce NDD progression and patient distress. However, no minimally invasive diagnostic tools existed for either conventional or new disease biomarkers. Instead, analysis was performed on cerebral spinal fluid (CSF) obtained from a lumbar puncture procedure which was time consuming, invasive and limited in terms of widespread application.

Potential biomarkers for AD and PD, such as the stress hormone cortisol, could not be analysed directly from blood samples but required purification or, in the case of the AD markers a-synuclein and the pathogenic protein Tau, lacked measurement traceability.
Another method of monitoring NDD progression, particularly the decline in cognitive function and increase in psychological symptoms such as agitation and anxiety, was the use of ‘Person-centred Outcome Measures’ (PCOMs). However, conventional methods for developing PCOMs lacked measurement comparability, SI traceability and the analysis of measurement uncertainties required for the development of clinical thresholds for early NDD diagnosis, essential to inform appropriate healthcare decision making.


This project helped to address the needs for NDD measurements by exploring innovative techniques for early diagnosis and monitoring. This involved the establishment of two patient cohorts, one with ‘mild cognitive impairment’ and AD patients and the second with both AD and PD patients.

For patients and healthy control subjects in the first cohort minimally invasive methods, such as   blood or saliva samples, were compared to measurements from spinal fluid samples. Nine protein and microRNA biomarkers were examined including t-Tau protein, α-synuclein and cortisol. Measurements were performed in conjunction with neurological imagining using Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy. This led to the development of a validated multimodal mathematical model for PCOMs termed ‘Construct Specification Equations’ (CSE). These allowed a patient’s cognitive memory ability to be described as a function of several explanatory variables, for the first time linking cognitive assessment outcomes to metrologically validated clinical biomarkers. In addition, preliminary SI traceable reference methods were developed for Tau protein in CSF and blood and for a- synuclein in CSF and saliva.

The second cohort allowed the establishment of a new method to directly measure cortisol in blood without the need to isolate it first. Results indicated it might be possible to use this technique to distinguish between PD and AD and healthy subjects.


To accelerate the uptake of these new techniques into clinical settings work was continued in the EMPIR project NeuroMET2 developing validated reference methods for AD and PD biomarkers. Studies will also continue on patient groups to further consolidate the applicability of CSE for standardisation of PCOMs, essential to underpin reliable clinical decisions for early disease diagnosis and recruitment in clinical trials.



Coordinator: Milena Quaglia (LGC) 


For more information, please contact the EURAMET Management Support Unit:

Phone: +44 20 8943 6666



Project website
Other Participants
Centre Hospitalier Universitaire Montpellier (France)
Charite - Universitaetsmedizin Berlin (Germany)
University College London (United Kingdom)
University of East Anglia (United Kingdom)


2016 - 2019