Defense Date


Document Type


Degree Name

M.S. Biological Sciences

First Advisor

Jose Lopez

Second Advisor

Francis De Piano


Alzheimer’s disease (AD) is the most common late-onset neurodegenerative disorder and cause of dementia, characterized by the formation of neurofibrillary tangles and senile plaque deposits. The heterogeneous nature of the disease (both genetically and environmentally) makes it difficult to prevent or cure. Without prevention, the prevalence of AD is expected to triple by 2050. However, because the diagnosis of AD is usually preceded by years of cognitive impairment, early detection may aid in reducing prevalence. Thus, there is a need for validated diagnostic measures for early and improved diagnosis and prevention. In this review, current and ongoing classifiers of early detection and tools for monitoring disease progression are discussed. In this present analyses, the diagnostic value of the following tools were statistically analyzed between three cognitive levels (cognitively normal, MCI, and AD) within (Alzheimer’s Disease Neuroimaging Initiative) ADNI databases: hippocampus volume, the Mini-Mental State Evaluation (MMSE) test, the Alzheimer’s Disease Assessment Scale (ADAS-Cog), APOE-ε4 genotype screening, and CSF biomarkers (including AB-42, P-tau, and T-tau). Hippocampal volumes were significantly different between cognitive groups over a 24-month period. These volumetric differences correlated to cognitive test scores, with ADAS-Cog 13 being more sensitive to time changes than the MMSE. APOE-ε4 genotype had only significant effects on hippocampal volume within MCI subjects, suggesting that the possession of the APOE-ε4 allele may have an effect on disease conversion. Of the biomarkers, Aβ42 yielded the highest sensitivity (84.09%) and negative predictive value (88.14%). Aβ42 /P-tau demonstrated the highest specificity (95.45%) and positive predictive value (91.18%). The combination of the several validated diagnostic tools (including hippocampal atrophy, cognitive screening tests, genotype, and CSF biomarkers) may increase the diagnostic accuracy of AD, possibly leading to improved diagnosis and reduction of AD prevalence.