Design of Nanorobots for an Early Detection of Alzhimer's Disease

Abstract

In this study, we propose a novel nanorobot model for the early detection of Alzheimer's disease. As a first step, we explored the polymorphism of the TREM2 gene's exons to assess its association with Alzheimer's. Our case-control study involved 124 Tunisian participants-64 Alzheimer's patients and 60 age-matched controls, averaging 67 years. Each participant underwent neurological evaluation, neuropsychological testing, brain imaging, and molecular analysis. Using Polymerase Chain Reaction (PCR) and sequencing techniques, we identified the rs2234253 variant in exon 2 and a novel intronic variant in intron 4, both of which were significantly correlated with Alzheimer's risk. Based on these genetic findings, we designed a nanorobot capable of detecting early biomarkers of Alzheimer's disease, such as amyloid plaques and tau tangles. The nanorobots are approximately 100 nm in size, enabling them to navigate the blood-brain barrier and specifically target regions of the brain affected by Alzheimer's pathology. They are constructed from biocompatible materials, such as gold nanoparticles and silica, and functionalized with surface receptors that selectively bind to Alzheimer's-related biomarkers. Equipped with nanosensors, the nanorobots are designed to detect binding events and transmit data to an external monitoring system in real time, facilitating early diagnosis and continuous monitoring of disease progression. These technological advancements offer a promising approach to enhancing Alzheimer's detection and improving patient out-comes.