An international research group has developed a groundbreaking fibre optic method that allows the build-up of amyloid plaques in the brains of living, freely moving mice to be monitored in real time. This innovative approach offers new perspectives for research into the progression of Alzheimer's disease and the effectiveness of potential treatments.
The study describes how researchers from the University of Strathclyde and the Italian Istituto Italiano di Tecnologia have adapted an existing technique, fibre photometry, to make amyloid plaques visible. Whereas fibre photometry is normally used to measure neural activity via genetic sensors, the researchers are now using Methoxy-X04: a fluorescent dye that crosses the blood-brain barrier and binds specifically to amyloid fibrils.
From flat fibres to depth profiles
In an initial series of experiments, flat optical fibres were placed in the brains of anaesthetised mouse models for Alzheimer's disease (5xFAD mice). The fluorescence signals obtained were found to correlate strongly with the plaque density in brain sections that were subsequently analysed. Using a machine learning model, researchers were able to accurately distinguish between diseased and healthy mice based on these signals.
A more advanced variant was then tested: tapered optical fibres that can pick up signals from different depths in the brain. In brain tissue, these fibres showed reliable results in terms of plaque distribution. When implanted chronically in living mice, the fibres detected depth-dependent increases in fluorescence after injection with Methoxy-X04, but only in mice with Alzheimer's disease and not in healthy control animals.
Towards long-term, non-invasive monitoring
An important advantage of this method is that it can be used in awake, freely moving animals. Unlike existing imaging techniques such as two-photon microscopy or optoacoustic tomography, this fibre-optic-based approach does not require anaesthesia and offers possibilities for long-term monitoring of deeper brain structures.
Although the technique cannot (yet) distinguish individual plaques, the researchers argue that it is a promising, minimally invasive way to track pathological changes in the brain over time and at different locations. This opens the door to more dynamic test setups for evaluating Alzheimer's therapies. The study was recently published in the journal Neurophotonics
According to the authors, this technology could play an important role in preclinical research, as scientists are now able to monitor in real time how quickly amyloid plaques build up and how effectively experimental treatments may slow down this development. The method thus contributes to accelerating therapy development and improving our understanding of disease progression in Alzheimer's.
AI and Alzheimer's diagnostics
A couple of weeks ago we reported about a research team from Singapore’s National University Health System (NUHS) that launched a S$2.33 million project to improve early dementia detection and care using predictive AI and personalized health coaching. Dementia is significantly underdiagnosed in Singapore, over half of cases go undetected, according to the 2023 WiSE study, despite evidence that 45% of cases could be prevented with early intervention.
The project, called IMPROVE-COG, will develop an AI-powered large language model (LLM) using anonymized hospital data to identify patients at risk of mild cognitive impairment or dementia. This tool will support more accurate and cost-effective diagnoses. Researchers will also study the influence of environmental and social factors on cognitive health using geographic information systems.
