Cheap, Non-Invasive Blood Test Predicts Alzheimer's Risk 20 Years Ahead of Symptoms

Conventional methods for early detection are not only costly but also invasive, typically involving procedures like lumbar punctures that are both physically and emotionally strenuous for the patient. Now, a simple, cheap, and non-invasive blood test may be capable of assessing the likelihood of someone developing Alzheimer's up to two decades before any symptoms appear.

A team of physicists from The Australian National University (ANU, Canberra, Australia) has combined nanotechnology and artificial intelligence (AI) to analyze proteins in the blood for early indicators of neurodegeneration, or specific "biomarkers" signaling the onset of Alzheimer's. Proteins are essentially the foundation of life, containing unique genetic blueprints for each person that offer valuable insights into our health, including the degeneration of brain cells. Locating these proteins with early neurodegeneration markers is like finding a needle in a haystack, according to the researchers.

To tackle this, physicists at ANU have developed an ultra-thin silicon chip embedded with "nanopores," or tiny nanometer-sized holes, that single out proteins for analysis with the aid of a sophisticated AI algorithm. A tiny blood sample is placed on the silicon chip, which is then put into a handheld device roughly the size of a smartphone. This device employs the AI algorithm to sift through the blood sample for protein markers indicative of early-stage Alzheimer's. Notably, the researchers say that the algorithm has the potential to be adapted to screen for various neurological conditions concurrently, such as Parkinson's disease, multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS). The ANU scientists anticipate that this screening method could become accessible within the next five years. The study has been published in the journal Small Methods.

"Blood is a complex fluid that contains more than 10,000 different biomolecules. By employing advanced filtration techniques and harnessing our nanopore platform, combined with our intelligent machine learning algorithms, we may be able to identify even the most elusive proteins," said ANU Ph.D. researcher Shankar Dutt.

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