An overview of Alzheimer's disease and its diagnosis using conventional and novel methods

Abstract

Alzheimer's Disease (AD), a progressive neurodegenerative disease caused by abundant abnormal extracellular amyloid-β plaques and intracellular assemblage of tau inclusions, can severely affect the living of patients as it causes dementia. As aging is the most important risk factor of AD, an increasing aging global population will lead to more serious problems in the future. The progression of AD includes three stages: the asymptomatic stage, Mild Cognitive Impairment and dementia. At present, most diagnoses methods are focused on MCI and dementia stages of the disease as disease during the asymptomatic stage is challenging. At present, effective diagnostic methods include neuropathological diagnosis that focus on the macroscopic features and microscopic features of AD, biomarkers such as cerebrospinal fluid biomarkers and other biomarkers in the human plasma, imaging techniques including structural magnetic resonance imaging and F-fluorodeoxyglucose-position emission tomography, psychological and behavioral tests, etc., but most of them have obvious deficiencies. Novel diagnostic methods, such as saliva biomarkers, which cost less and are more accurate in diagnosing AD can have promises for early diagnosis of AD, leading better patient outcomes. With the advancement of emergence of technologies, such as artificial intelligence, more effective diagnosis methods will be available, and the efficiency of diagnosing AD will increase, benefiting patients and their families. This paper provides an overview of AD and investigates conventional and novel methods for its diagnosis.