Author: Daniel Tran
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) provides researchers with a vast amount of genetic, cognitive test results, biomarkers and MRI image data on patients in various stages of Alzheimer's disease and other mental cognitive disorders. This a large scale multifaceted longitudinal case-control study focused on identification of new risk factors for AD and better understanding of time of onset, progression rates and diagnosis decisions. A more complete risk factor knowledge and AD comprehension will greatly improve our ability to predict a subject-specific susceptibility, age of development and rates of decline. We propose to study one of the most interesting and difficult questions, estimating the rates of progression while adjusting for all relevant genetic, environmental, and image-based confounders and effect modifiers that have become known due to already completed research. We have designed and will implement a longitudinal analyses using mixed effects modeling that will allow us to properly account for the correlation structure of repeated measurements on the same subjects. Our results will reveal a new and complete list of predictors for rate of progression of AD as well as assess the corresponding unbiased effect sizes.
Co Author/Co-Investigator Names/Professional Title: Daniel Tran (MS Computational Science student) Chapman Dr. Cyril Rakovksi, Professor Chapman University