The number of patients diagnosed with Alzheimer’s disease is growing at an epidemic rate, but early diagnosis continues to pose a major challenge. Currently, preclinical detection of the disease requires a painful lumbar puncture to observe unusual protein levels in the patient’s cerebrospinal fluid. EU project SensApp brings together several scientific groups from across Europe to collaborate on the development of a super-sensor, which could enable a new, more humane way for Alzheimer’s disease discovery and continuous monitoring.
Alzheimer’s disease, which is the most common cause of dementia, causes abnormal amount of proteins called amyloid and tau to accumulate into the patient’s brain. The detection of these proteins requires a lumbar puncture to observe protein levels in the cerebrospinal fluid. The detected protein levels indicate whether patient has Alzheimer’s disease and if so, how the disease is progressing in time. Unfortunately, the painful sample intake prohibits arranging easy and highly efficient screening programs among the population, and thus Alzheimer’s disease is typically diagnosed at a later stage, when it has started to present with memory problems or other symptoms of cognitive impairment.
SensApp project aims to develop a super-sensor, which would be able to detect these proteins in human plasma from a simple blood sample. This requires detection sensitivity reaching below 1 pg/mL, which is currently not reached using standard test protocols. In simple terms, this means developing a combination of novel detection and dispensing technologies that together can measure very low concentrations of proteins related to Alzheimer’s disease in human plasma. The development of the new diagnostic method requires a strong set of cross-disciplinary expertise, and it brings together biochemists, physicists, engineers and health care professions. Each partner brings to the table their own strengths and background.
“The project brings together very different expertise ranging from physics and engineering to biology and clinical sciences. We aim at building a prototype instrument able to make easy and rapid diagnosis of Alzheimer’s disease (AD). This will change radically the perspectives of clinicians, since tests for new therapies will be possible in the early stage of the disease, before the appearance of recognizable symptoms that usually correspond to irreversible brain damages”, says the project coordinator, Dr. Simonetta Grilli.
Towards a functioning super-sensor prototype
Currently, the research focuses on developing a novel super-sensor prototype. The prototype builds on a completely new technology called here “droplet-split-and-stack” (DSS), developed by the research team of the project coordinator in Cnr (Institute of Applied Sciences and Intelligent Systems).
“In very simple terms, we can say that we are using an electric field to stack tiny droplets of plasma on top of each other to create a locally intense signal through a reaction between the protein biomarker and the corresponding labelled antibodies. This way we can detect volumes that have previously been undetectable. The results are then analysed using a fluorescence laser scanning module.”
“We have already tested successfully in Cnr the sub-picogram sensitivity of the DSS technology in case of model samples. The upcoming challenge is to detect the Alzheimer’s disease biomarkers with the same sensitivity in real plasma samples” says Simonetta Grilli.
The new technology developed by SensApp will be available also for other fields of medicine where the doctor searches for low abundant antibodies and protein-based biomarkers in the early stage of the disease, for example in oncology, or for heart- and stress-related disease and covid. Next year the project will move into a testing phase and start using the new automated units for testing plasma samples for the detection of amyloid and tau proteins.
The final target of the project is that this super-sensor will enable a fast and early diagnosis of AD through a routine blood test at your local physician’s clinic.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme.
CNR - Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello"
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