Periodic Reporting for period 2 - BBDiag (Blood Biomarker-based Diagnostic Tools for Early Stage Alzheimer’s Disease)
Período documentado: 2019-01-01 hasta 2021-12-31
The aim of the BBDiag project was to train a new generation of ESRs for early AD diagnosis based on blood biomarkers. Despite of the notable recent advances in AD biomarkers and diagnostics, dementia is still one of the Societal Challenges listed by the UN and EU. BBDiag responded to such a need and established this ETN for blood based early-AD diagnostics. BBDiag Fellows were trained under the Vitae Researcher Development Framework innovatively combined with the BBDiag platform for gaining interdisciplinary skills as well as personal quality, creative thinking and business mind-set. The ETN had a highly innovative research programme for the discovery of AD biomarkers, development of novel biosensing techniques and point of care tools, and for technological exploitation of the diagnostics. These advances will strongly support improved care provision and development of disease-modifying treatments and preventive strategies for AD patients. More importantly, BBDiag delivered its first generation of highly-skilled, creative and entrepreneurial Fellows, setting them on a path to successful careers in academia or industry to ensure that the medical and societal challenges imposed by AD are met.
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.
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.
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 tau355 AD blood biomarkers, the lowest reported with a label-free biosensor.
Ultra-sensitive digital ELISA multiplexing biosensors with limit of detection at 10 aM were developed with integration of 3D printed microfluidics of 16 channels. A clean-room-free process that can be employed in a conventional chemical lab was also developed for the fabrication of these devices.
Controlled deposition of 1,5-diaminonaphthalene (DAN) has been achieved on CVD graphene surfaces. The experimental results evidenced that the electrochemical sensing efficiency increases, owing to the synergistic effects of better electron transfer as well as higher enzyme loading on DAN modified electrodes. Detection of typical protein AD biomarkers using graphene biosensors have also been demonstrated.
Validity of an in vivo amyloid staging model was evaluated in an independent cohort of elderly people with subjective memory complaints (SMC) and further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer’s disease (AD). Our results showed that neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort.
PoC devices for AD diagnosis are of high clinical relevance given the current development of potentially disease modifying treatments. These treatments require a biomarker confirmed diagnosis of amyloid positive Alzheimer’s disease by PET or CSF. The first such treatment, the amyloid antibody aducanumab (marketed under the name of Aduhelm), has been approved by the FDA in June 2021. Delivering these treatments will benefit from the preselection of high risk patients at point of care using blood biomarkers. This will help more efficient diagnosis of patients and more selective assignment of people at risk to in depth CSF or PET diagnostic. The nanomaterial based multiplex assays are of additional value given their possibility to detect several key markers of Alzheimer’s disease at the same time and combine markers of Alzheimer’s pathology, such as amyloid, with markers of Alzheimer’s disease dynamics, such as NFL, that will allow a more precise prediction of future disease course in a single individual than each marker alone. At the same time, this technology in future will allow robust measurement of multiple blood markers even outside specialized settings at relatively low costs compared to currently available blood markers that require complex preprocessing and storage of blood samples.
Ultra-sensitive digital ELISA multiplexing biosensors with limit of detection at 10 aM were developed with integration of 3D printed microfluidics of 16 channels. A clean-room-free process that can be employed in a conventional chemical lab was also developed for the fabrication of these devices.
Controlled deposition of 1,5-diaminonaphthalene (DAN) has been achieved on CVD graphene surfaces. The experimental results evidenced that the electrochemical sensing efficiency increases, owing to the synergistic effects of better electron transfer as well as higher enzyme loading on DAN modified electrodes. Detection of typical protein AD biomarkers using graphene biosensors have also been demonstrated.
Validity of an in vivo amyloid staging model was evaluated in an independent cohort of elderly people with subjective memory complaints (SMC) and further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer’s disease (AD). Our results showed that neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort.
PoC devices for AD diagnosis are of high clinical relevance given the current development of potentially disease modifying treatments. These treatments require a biomarker confirmed diagnosis of amyloid positive Alzheimer’s disease by PET or CSF. The first such treatment, the amyloid antibody aducanumab (marketed under the name of Aduhelm), has been approved by the FDA in June 2021. Delivering these treatments will benefit from the preselection of high risk patients at point of care using blood biomarkers. This will help more efficient diagnosis of patients and more selective assignment of people at risk to in depth CSF or PET diagnostic. The nanomaterial based multiplex assays are of additional value given their possibility to detect several key markers of Alzheimer’s disease at the same time and combine markers of Alzheimer’s pathology, such as amyloid, with markers of Alzheimer’s disease dynamics, such as NFL, that will allow a more precise prediction of future disease course in a single individual than each marker alone. At the same time, this technology in future will allow robust measurement of multiple blood markers even outside specialized settings at relatively low costs compared to currently available blood markers that require complex preprocessing and storage of blood samples.