Shedding light on proteins linked to Alzheimer’s disease to enable earlier detection of the disease

Many neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease, are difficult to diagnose before symptoms begin to appear. However, disease-related biomarkers, such as aggregated proteins called amyloids, could provide important information much earlier, if they can be easily detected. Researchers publishing in ACS sensors developed such a method using a set of sensor molecules capable of illuminating amyloids. The tool could help monitor disease progression or distinguish between different amyloid-related conditions.

Neurodegenerative diseases typically involve a breakdown in communication in the brain that is often caused by “sticky” clumps of misfolded proteins called amyloids that interrupt signal transfer. These amyloids are thought to be closely linked to the progression of Alzheimer’s disease and therefore could be used as a means of early diagnosis to expand treatment options.

Currently, radio imaging techniques, including positron emission tomography (PET), can detect amyloids, but these methods rely on sophisticated equipment and typically focus on one of several amyloids involved in the disease. Instead, fluorescence imaging techniques have been explored as a simpler, but still sensitive, way to detect multiple specific amyloids.

So, Margaret Sunde, Elizabeth New, Amandeep Kaur and their colleagues wanted to develop a network of fluorescent sensors for amyloids to monitor the progression of Alzheimer’s disease and other diseases and to distinguish these atypical amyloids from similar proteins forming amyloid of natural origin.

The team combined five coumarin-based molecular probes, each of which fluoresced to a different degree when it encountered the amyloids, into a sensor array. However, the team found that using just two of the probes with the strongest fluorescence responses still provided a high level of sensitivity and an identifiable fluorescent “fingerprint” for individual amyloids.

The two-probe array was added to a sample mixture mimicking biological fluids containing molecules that could interfere with detection. Regardless, the network retained high sensitivity and selectivity. Its performance was also tested on samples taken from the brains of mouse models suffering from Alzheimer’s disease. The team observed that fluorescence patterns differed between early (at 6 months of age) and later (at 12 months of age) stages of the disease.

Additionally, a unique fluorescence fingerprint was generated for three amyloids commonly implicated in Alzheimer’s disease, another amyloid associated with the disease, and five naturally occurring “functional amyloids” not involved in the disease. The researchers say this tool could be used to distinguish closely related amyloids and could inform new approaches for earlier and more reliable diagnosis of amyloid-related diseases.