Project summary / Abstract
Alzheimer's disease (AD) is the most common form of age-related dementia. It is overwhelming 5.3 million
individuals71 and families in the US, 46.8 million people world-wide, and medical and health care systems.
Advances in research better identify prodromal phases (e.g., Mild Cognitive Impairment, MCI) although it
is unclear who will and who will not progress to AD. Prodromal phases are being classified using
neuroimaging and biospecimen biomarkers (e.g., amyloid and tau burden, regional atrophy). Yet,
cognitive changes are also occurring during prodromal phases, even 8-12 years prior to onset22,27. Our
challenge is choosing a cognitive marker that is sensitive to early disease change, corroborates with
underlying neuropathology, and can predict those who will convert. We propose one such measure,
namely the Serial Position Effect (SPE). We hypothesize that SPE markers are highly sensitive to AD, and
that they can predict conversion to AD from prodromal states.
We will retrieve cognitive and imaging data from the Alzheimer Disease Neuroimaging Initiative (ADNI)
dataset to investigate healthy adults, persons with mild cognitive impairment (MCI) who convert and do
not convert to AD, and persons with AD. SPE is a measure of word recall as a function of its position in a
word list, and measures will be calculated to generate profiles at learning and recall. AD performance
differs significantly from controls, corroborating their deteriorating semantic-memory systems. Aim 1: We
will demonstrate unique associations between characteristic SPE markers at learning and delay recall and
underlying neurodegenerative biomarkers including regional atrophy, cortical thinning, amyloid and tau
burden. Aim 2: We will test the predictive strength of SPE markers to establish the relative risk of
developing disease given SPE profile characteristics.
The significance of the study is that if SPE markers corroborate with underlying neurological biomarkers
of AD, and predict the elevated risk to conversion to AD, SPE can serve as a functional and cost-effective
tool for disease prediction, detection, and potentially for drug efficacy. Also, as SPE measures are easily
derived from any list, they can be culture-free and not dependent on linguistic differences.
The project's first innovation is that despite hundreds of ADNI investigations, none have applied SPE
analyses. Second, this approach shifts a prevalent practice of using non-specific cognitive tasks to
adopting a cognitive instrument that is theoretically-driven and corroborated by underlying disease-specific
neurological processes of AD.