Design of a Nanorobots for an Early Detection of Alzhimer’s Disease

Abstract

Alzheimer’s disease is characterized by two Key pathophysiological features, which are neurofibrillary tangles and senile plaques. In this study, we propose a novel nanorobot model aimed at the early detection of Alzheimer’s disease. As an initial step, we conducted an experimental investigation into the polymorphism of the TREM2 gene’s exons to determine allelic and genotypic frequencies, highlighting its correlation with Alzheimer’s disease. Our case-control study involved a sample of 124 Tunisian subjects, divided into two groups: 64 patients diagnosed with Alzheimer’s and 60 age-matched controls, averaging 67 years. Each participant underwent a comprehensive neurological examination, neuropsychological assessment, brain imaging, and molecular analysis. For the genetic component of our study, we employed PCR and sequencing techniques, identifying the rs2234253 variant in exon 2 and a novel intronic variant in intron 4. Our findings indicate that the TREM2 gene significantly contributes to the risk of developing Alzheimer’s disease. Based on these results, we present our proposed nanorobot model designed for the early detection of this condition, detailing its potential applications in monitoring and diagnosis.