WP1 have successfully developed graphene and digital ELISA biosensors for PoC applications. A novel functionalisation technique for screen printed graphene biosensors was developed which can achieve a detection limit fM regime for the detection of AB1-40, AB1-42 and Tau-352 AD blood markers, the lowest reported with a label-free biosensor. The sensors have excellent linear dynamic range and specicifity in physiological solutions (human plasma). Sensors were also stable for over 6 weeks. Ultra-sensitive 16 channel digital ELISA multiplexing biosensors with LOD at 10 aM were also developed. A clean-room-free process was also developed for the fabrication of these devices. A prototype PoC device is also achieved however the integration of the PoC devices with other techniques developed in the project was not possible mainly due to the negative impact of the COVID-19 pandemic.
In WP2, novel blood-based assays were developed, which would allow determination of whether vesicles coming from brain-related extracellular matrix are useful as biomarkers of AD. Furthermore, a novel sensitive platform was implemented to help address one of the major challenges, namely the low circulating levels of brain-derived molecules. AD biomarker discovery from exosome research has been carried out. Initial biomarker panels for early and clinical disease detection have been produced by machine learning and recommend them for testing on the BBDiag biosensors and further validations.
In WP3, we validated molecular, neuroimaging (MRI, PET), and neurophysiological (EEG) biomarkers in mouse and human models of AD. These biomarkers were progressively altered in relation to the age of those mouse models of AD and cognitive deficits. Furthermore, they were found to be abnormal in AD patients at several disease stages such as subjective memory complaints, mild cognitive impairment, and dementia. Advanced machine learning tools were implemented and validated using diagnostic biomarkers of AD derived from cerebrospinal fluid. The present results showed that a panel of molecular, structural, and functional biomarkers is able to model AD and represent a gold standard for the qualification of blood biomarkers of AD for the preliminary diagnosis of AD and the evaluation of the progression and responses to intervention from prodromal to clinical stages of dementia.
WP4 positioned itself within BBDiag project from its value chain perspective. By strategically positioning at the downstream of the value chain, WP4 focused its scientific work on the following in relation to the three tasks: identifying opportunities to access to markets and establishing links to the industry, developing ICT app to look into the links of people’s lifestyle such as smoking with AD, and building a business model that is market-oriented, resilient and robust for the exploitation of BBDiag platform.
Dissemination: our ESRs participated in a wide range of dissemination and communication activities, including scientific conferences, journal publications, sharing their methods and results with the scientific community and societal groups (patients, caregivers) and general public.
